C++ Projects on Upwork: Find Your Next Job

We are seeking a Senior Systems/Compiler Engineer to architect an LLVM-based domain-specific trading language. The role involves designing and implementing a compiler for a new programming language, focusing on performance, reliability, and maintainability. The ideal candidate will have experience with Rust and C++ and be familiar with compiler design and LLVM. This is a full-time position for a duration of 3 to 6 months.

We are seeking a skilled Robotics Software Developer to enhance our robotic systems. The ideal candidate will have experience in developing software for robotic applications. You will work closely with our team to design, develop, and test software solutions that improve the efficiency and functionality of our robots. If you have a passion for robotics and a strong background in software development, we would love to hear from you.

• We are looking for a long-term, full-time engagement with the right person — not a short project. Is that something you are open to and currently available for?
• What is your current notice period or earliest start date?
• What is your expected monthly rate for a full-time engagement?

I have a CAN-based hardware concept for trucks and excavators that still needs an expert eye and solid firmware. The board carries a CAN transceiver plus an as-yet-undecided microcontroller; your first job will be to review the schematic and component choices, making sure the design can reliably tap into a heavy-vehicle J1939 network.

Once the electronics check out, I need production-ready code that listens for multiple PGNs, performs light, on-board processing, and then forwards all remaining data to my back-end through a Bluetooth link. On the edge we have to handle three record types: sensor readings, diagnostic trouble codes, and operational parameters. Any PGN we do not actively process must be packed efficiently and shipped over Bluetooth for cloud processing, so memory management and timing will matter.

If you are comfortable selecting and configuring the right microcontroller tool-chain—Arduino, ESP32, STM32 or another that suits the job—while writing robust, well-documented C/C++ code with crystal-clear CAN filters and Bluetooth LE routines, I would like to work together. I will share the current schematic, parts list and J1939 message matrix once we start; I expect back a reviewed schematic with change notes, fully commented source, and a concise integration guide so my team can move straight to field testing.

Skills: Electronics, Microcontroller, PCB Layout, Arduino, Bluetooth, Embedded Systems, STM32, CAN Bus

Tôi cần một chuyên gia viết nội dung để tạo các mô tả sản phẩm thời trang hấp dẫn, ngắn gọn và đúng tông thương hiệu. Công việc bao gồm:

• Nghiên cứu nhanh đặc điểm sản phẩm (chất liệu, kiểu dáng, kích cỡ, ưu điểm) dựa trên ảnh hoặc thông tin tôi cung cấp.
• Viết mô tả sản phẩm chuẩn nội dung thương mại: câu mở thu hút, phần mô tả chi tiết, và lời kêu gọi hành động.
• Đảm bảo nội dung dễ đọc, không lỗi chính tả, tối ưu SEO cơ bản với từ khóa tôi sẽ gửi kèm.
• Giao file ở định dạng Word hoặc Google Docs, sẵn sàng để tôi sao chép lên website.

Tôi ưu tiên người từng viết mô tả cho quần áo, phụ kiện hoặc các sản phẩm fashion tương tự. Vui lòng gửi một-hai đoạn mẫu bạn đã viết để tôi đánh giá nhanh trước khi bắt đầu.

Skills: C Programming, Graphic Design, Copywriting, SEO, C# Programming, C++ Programming, Content Writing, Fashion Writing

We are seeking an experienced Embedded Systems / Firmware Engineer to design the electronic architecture and write the control code for a functional proof-of-concept (PoC) bench prototype.

The project involves building a closed-loop temperature control system utilizing off-the-shelf development boards and modules. No custom PCB design or physical enclosure fabrication is required for this milestone.

Technical Architecture:
• MCU: ESP32 Development Board.
• Actuation: NEMA 17 stepper motor driven by a quiet stepper module (e.g., TMC2209 or equivalent) to mechanically modulate a standard rotary D-shaft valve.
• Feedback: A K-type thermocouple feeding real-time data via an SPI/I2C amplifier module (e.g., MAX31855).
• Control Theory: A robust PID loop structured to handle substantial thermal lag/inertia from a heavy steel mass.

Your Deliverables:
1. BOM Validation & Wiring Diagram: Verify our component selection and provide a clear schematic/breadboard wiring layout.
2. Firmware Development: Write clean, well-commented C/C++ code (Arduino IDE or ESP-IDF framework) managing data acquisition, moving-average sensor filtering to eliminate noise, and smooth stepper positioning.
3. Adaptive PID Tuning: Implement a PID structure capable of handling slow-response thermal environments without severe oscillation (incorporating manual profile swapping or gain scheduling for external environment changes).
4. Safety Fail-Safes: Code watchdog logic (e.g., system shutdown if the sensor fails, disconnects, or fails to detect a temperature rise within a specific timeframe while the valve is open).

Required Qualifications:
• Proven experience with Embedded C/C++ and the ESP32 platform.
• Strong understanding of stepper motor control (acceleration, microstepping, and position tracking).
• Experience implementing PID control loops for high-thermal-mass systems.
• Experience with sensor filtering algorithms (Low-Pass or Moving Average).

Project Scope & Milestones:
This contract is focused strictly on achieving a working desktop bench prototype. We will handle the physical mechanical coupling and CAD modeling on our end. You will provide the code and remote support/debugging as we calibrate the loop on our hardware.

This project will be structured into 3 fixed-price milestones:
1. BOM Validation & Wiring Schematic Approval
2. Core Firmware Delivery (Functional Desktop Bench-Test)
3. Remote Calibration & Final PID Tuning Assistance

Please apply with examples of past projects involving automated motor control, closed-loop thermal regulation, or mechatronic prototyping.

We have a Chromium based browser and need to update it for both Mac & Windows. All the patches need to be integrated into the latest Chromium then if there isn't a match or there's a bug or the functionality isn't correct, it must be fixed. All our old patches / functionality must be successfully integrated. We will guide you on any Mac / Windows build differences.

You should have a relatively powerful machine that can run Chromium builds.

You can use AI tools to do a lot of the work, but you'll need to have reasonable coding and Chromium skills to manage the whole project.

We will continue to do updates for desktop as well as for mobile, so there is definitely the possibility of more work if you do good work.

Hello,
do you have any experience with Vinted. It’s about finding specific endpoints. There are bots with zero delay and others without, and there’s also a Vespa cache; someone really needs to do a thorough search for it.

# Rocket Propulsion System Design & Analysis Project – Capability Assessment Request

Hi

I am looking for an aerospace engineer, propulsion engineer, researcher, or consultant with strong expertise in liquid rocket propulsion to support a comprehensive propulsion engineering project.

Before discussing pricing or timelines, I would like to understand whether you possess the required technical background, software proficiency, and project experience to execute a project of this scope.

This is not a simple academic assignment. The objective is to perform a complete conceptual and preliminary design study of a liquid rocket engine and associated propulsion subsystems using industry-standard methodologies and software.

---

# Project Objective

The goal is to develop a complete propulsion engineering package for a liquid rocket engine from initial requirements through preliminary design, analysis, and verification.

The project should demonstrate the workflow used by propulsion engineers working in organizations such as:

* SpaceX
* Blue Origin
* Rocket Lab
* European Space Agency
* NASA
* ArianeGroup

This project is intended as a propulsion engineering portfolio, learning exercise, and engineering demonstration project.

The project should follow professional aerospace engineering standards, assumptions, documentation, calculations, analyses, and design methodology.

---

# Desired Engine Type

The consultant should be capable of designing and analyzing one or more of the following:

### Option 1

LOX/RP-1 Liquid Rocket Engine

### Option 2

LOX/Methane Liquid Rocket Engine

### Option 3

LOX/LH2 Liquid Rocket Engine

The final selection can be discussed based on feasibility and educational value.

---

# Required Technical Scope

The project should include as many of the following areas as possible.

---

# 1. Mission Requirements Definition

Development of:

* Mission objectives
* Vehicle assumptions
* Delta-V assumptions
* Thrust requirements
* Burn duration
* Propellant selection rationale
* Chamber pressure targets
* Mixture ratio selection
* Performance goals

Deliverables:

* Requirements document
* Design assumptions document
* Mission analysis report

---

# 2. Propellant Selection Trade Study

Comparison of:

* LOX/RP-1
* LOX/Methane
* LOX/LH2

Evaluation criteria:

* Specific impulse
* Density impulse
* Storage complexity
* Cost
* Reusability
* Cooling considerations
* Manufacturing considerations

Deliverables:

* Trade matrix
* Selection justification

---

# 3. Thermochemical Analysis

Use of:

* NASA CEA

Required outputs:

* Adiabatic flame temperature
* Molecular weight
* Characteristic velocity
* Vacuum Isp
* Sea-level Isp
* Equilibrium performance
* Frozen performance

Deliverables:

* Input files
* Output reports
* Interpretation of results

---

# 4. Engine Cycle Selection

Trade study between:

* Pressure-fed
* Gas generator
* Expander cycle
* Staged combustion
* Full-flow staged combustion

Required analysis:

* Advantages
* Disadvantages
* Complexity
* Cost
* Risk

Deliverables:

* Engine cycle selection report

---

# 5. Rocket Engine Sizing

Complete preliminary sizing calculations:

* Thrust
* Mass flow rate
* Chamber pressure
* Mixture ratio
* Expansion ratio
* Characteristic length
* Chamber dimensions

Deliverables:

* Calculation workbook
* Engineering report

---

# 6. Injector Design

Analysis of:

* Showerhead injectors
* Impinging injectors
* Pintle injectors
* Coaxial injectors

Deliverables:

* Selection rationale
* Preliminary sizing
* Injector geometry

---

# 7. Combustion Chamber Design

Design and sizing of:

* Chamber geometry
* Chamber length
* Chamber diameter
* Residence time
* L* calculations

Deliverables:

* Engineering calculations
* CAD model

---

# 8. Nozzle Design

Design of:

* Convergent section
* Throat
* Divergent section

Analysis of:

* Bell nozzle
* Conical nozzle

Required calculations:

* Expansion ratio
* Area ratio
* Exit pressure
* Exit velocity

Deliverables:

* Geometry definition
* CAD model
* Performance report

---

# 9. Regenerative Cooling Analysis

Required:

* Cooling channel concepts
* Heat transfer calculations
* Thermal load estimation
* Coolant pressure drop

Deliverables:

* Thermal report
* Cooling analysis report

---

# 10. Turbomachinery Design (if applicable)

Preliminary design of:

* Fuel pump
* Oxidizer pump
* Turbine

Required calculations:

* Pump power
* Turbine power
* Pressure rise
* Rotational speed

Deliverables:

* Preliminary turbomachinery sizing report

---

# 11. Feed System Design

Development of:

* Tanks
* Feed lines
* Valves
* Pressurization systems

Deliverables:

* Feed system schematic
* Mass estimates

---

# 12. Piping and Instrumentation Diagram (P&ID)

Creation of:

* Complete propulsion architecture

Including:

* Valves
* Sensors
* Pumps
* Tanks
* Flow paths

Deliverables:

* P&ID drawing

---

# 13. CAD Development

Software preferred:

* SolidWorks
* CATIA
* Siemens NX
* Fusion 360

Expected models:

* Injector
* Chamber
* Nozzle
* Feed system
* Assembly model

Deliverables:

* Native CAD files
* STEP files
* Technical drawings

---

# 14. CFD Analysis

Software:

* ANSYS Fluent
* ANSYS CFX
* OpenFOAM
* STAR-CCM+

Potential analyses:

### Internal Flow

* Chamber flow
* Nozzle flow

### Thermal Analysis

* Heat flux
* Wall temperature

### Combustion Analysis

* Simplified combustion modelling

Deliverables:

* Mesh files
* Solver setup
* Results
* Validation discussion

---

# 15. Finite Element Analysis (FEA)

Software:

* ANSYS Mechanical
* Abaqus
* Nastran

Analysis:

* Pressure loading
* Thermal loading
* Structural integrity
* Safety factor

Deliverables:

* FEA report
* Stress plots
* Deformation plots

---

# 16. EcosimPro Modelling

Preferred if consultant has experience.

Required:

* Propulsion system architecture
* Dynamic simulation
* Start-up transient analysis
* Feed system simulation

Deliverables:

* EcosimPro model
* Simulation results

---

# 17. System-Level Modelling

Software:

* MATLAB
* Simulink
* Python
* EcosimPro

Analysis:

* Performance simulation
* Sensitivity analysis
* Parametric studies

Deliverables:

* Model files
* Technical report

---

# 18. Verification and Validation

The consultant should explain:

* Assumptions
* Limitations
* Validation methods
* Comparison with literature

Deliverables:

* Validation report

---

# 19. Mass Budget

Development of:

* Propellant masses
* Structural masses
* Feed system masses
* Engine masses

Deliverables:

* Mass budget spreadsheet

---

# 20. Failure Mode Analysis

Preliminary FMEA covering:

* Combustion instability
* Turbopump failure
* Thermal failure
* Structural failure
* Feed system failure

Deliverables:

* Risk assessment report

---

# Software Experience Required

Please indicate your level of proficiency with:

### Thermochemistry

* NASA CEA
* RPA (Rocket Propulsion Analysis)

### CAD

* SolidWorks
* CATIA
* Siemens NX

### CFD

* ANSYS Fluent
* ANSYS CFX
* OpenFOAM
* STAR-CCM+

### FEA

* ANSYS Mechanical
* Abaqus
* Nastran

### System Simulation

* EcosimPro
* MATLAB
* Simulink

### Programming

* MATLAB
* Python

---

# Deliverables Expected

The final project should ideally include:

### Documentation

* Full engineering report
* Design report
* Trade studies
* Validation reports

### Engineering Calculations

* Rocket performance calculations
* Feed system calculations
* Thermal calculations
* Structural calculations

### CAD

* Complete CAD package

### CFD

* CFD package
* Results
* Reports

### FEA

* Structural package
* Reports

### Simulation

* EcosimPro model
* MATLAB models

### Management Documents

* Statement of Work (SOW)
* Work Breakdown Structure (WBS)
* Deliverables Matrix
* Acceptance Criteria

---

# Questions for the Consultant

1. What is your educational background?

2. Have you worked on rocket propulsion projects before?

3. Have you designed liquid rocket engines?

4. Which propulsion cycles have you worked with?

5. Which of the listed software tools can you use professionally?

6. Can you perform NASA CEA analysis?

7. Can you perform CFD of combustion chambers and nozzles?

8. Can you perform FEA under thermal and pressure loads?

9. Can you develop EcosimPro propulsion models?

10. Can you create complete CAD assemblies?

11. Which portions of the project can you personally complete and which would require subcontracting?

12. Could you provide examples of similar propulsion, aerospace, turbomachinery, CFD, or thermal-fluid projects you have completed?

13. What deliverables would you realistically be able to provide?

14. What timeline would you estimate for completion?

15. What budget range would you estimate for a project of this scope?

Please be candid regarding your experience level, software capabilities, and the portions of the project you would feel comfortable delivering to a professional engineering standard. This will help determine whether there is a good fit for collaboration.

We are looking for a senior software engineer with strong experience in C#/.NET and C++ to work on production systems that combine desktop applications, backend services, and system-level components.

A portion of the system operates in a healthcare and medical imaging context, where software reliability, data accuracy, and interoperability are important. This includes working with structured clinical data and integration-heavy workflows where multiple systems need to communicate reliably.

The codebase is a mix of modern .NET (Core / 6 / 8) services, older .NET Framework components, and C++ modules used in performance-sensitive or legacy areas. You will be working across all of these layers, often tracing issues end-to-end from desktop UI through APIs and into backend or native components.

This is not a greenfield project. The system is already in production, so the focus is on stability, safe improvements, debugging complex issues, and gradually modernizing parts of the architecture without disrupting existing functionality.

The ideal engineer is someone comfortable working in mixed technology environments, including legacy systems, and who can understand how data flows across desktop, backend, and native layers. Experience in healthcare or medical imaging systems is a strong plus, but not required.

We are seeking skilled programmers and developers to join our team. The ideal candidates will have experience in Android app development, PHP, HTML5, and JavaScript. You will be responsible for developing and maintaining software applications, collaborating with cross-functional teams, and ensuring high-quality deliverables. If you are passionate about coding and have a strong work ethic, we would love to hear from you.

Hi! Thanks for taking part in this research session.
You'll be shown a prototype of the Swipix app — a watch-to-earn mobile app where users earn DOPPY tokens by watching videos.
Please open the prototype link below on your phone or browser and follow the steps. This takes about 3 minutes.

Steps:
Open the prototype link provided for your group: https://doppy-market-prototype.pages.dev

You see the Balance screen. You have 1 DOPPY and 100 LUMY. Imagine this is your real account.
Tap the WITHDRAW button in the top right.
A new screen appears. Read it carefully — take your time
Decide what you would do next.
Answer the questions in this form: https://docs.google.com/forms/d/11Fk3HjfRyqsHVbzzm9uQE0_4BVy7FEjqAv9CQBuDuC4/edit

I need someone who can jump into my Schneider M340 PLC, pull down the current program, and pinpoint why the machine went into auto-stop. The fault appears to be an electrical issue rather than software or pneumatics.

Here’s what I’m looking for:
• Remote connection to the M340 (Unity Pro / EcoStruxure)
• Quick review and backup of the running logic
• Identification of the exact auto-stop trigger and the related I/O or protections
• Clear explanation of the fault and the corrective action taken (or wiring changes I should ask my electrician to handle)
• Confirmation that the error is cleared and the line restarts normally

You must be comfortable working live on Schneider PLCs and documenting every change you make. As soon as we’re back up and running, payment is released immediately—no delays.

Skills: C# Programming, Software Architecture, Electrical Engineering, C++ Programming, Unity 3D, Process Automation, Automation, PLC

I am looking for a developer who can develop USDT Flashing Software in main network (windows based, preferably windows 10 or 11).

Key Requirements:

1) The software can generate flash of the USDT, as well as the flashed USDT should be transferable from/to unlimited wallets with blockchain confirmations is appreciated. Since it is flash usdt it must be visible in usdt wallet address for 90 days. There will be no limitation for daily transfer for USDT It can’t be tracked as fake transaction. Should take normal time to send usdt one wallet to another wallet in normal internet connection.

2) There should be no limit on how much Flash USDT can be created. There will be no limitation for daily transfer for usdt and there will be work P2P tradeable,
These USDT wil be trade-able, swappable and transferable.

3) These USDT will disappear after 90 days.
Note:- The Flash USDT should have a minimum lifespan of 10 days and there is a option to choose between 10 and 90 days. (negotiable)

4) There should be an option to select which crypto currency end-user want to flash. (USDT, BTC, ETH and TRX) Compatible with all USDT networks (TRC20 , ERC20 , BEP20 , BEP2 , SOLANA , POLYGON)

5) Transaction Confirmation: All Flash USDT transactions must show 100% confirmation, with the transaction status marked as "success" on blockchain explorers.

6) Wallet & Exchange Compatibility: The Flash USDT must be transferable to all types of wallets and exchanges without any restrictions.

7) Visibility: The Flash USDT balance must be visible on the recipient's wallet under their actual USDT balance.

8) Preferred Network: The Flash USDT should operate on the TRC20 (Tron) network.

9) Testing: I require rigorous testing to ensure the best functionality of the software. You should test it on your internal protocols.

10) Payment terms: When you have tested the software, I do a final test in which you have to send 100 flash USDT to my given address so that I can check on explorer if everything is ok with my requirements. Then I give you 50% of the total amount and 50% of the total amount when the delivery is successful.

I am open for discussions and We can discuss about more in chat.

Skills: PHP, C Programming, Python, Software Architecture, C++ Programming

I am putting together an instructional animation and need a five-person AI task-force to power the technical side of the production. The core roles are Machine Learning Experts, Data Scientists, and Computer Vision Specialists—ideally people who feel at home moving between Python notebooks, TensorFlow / PyTorch stacks, and OpenCV pipelines.

Your main focus will be data analysis and algorithm development. Concretely, I’ll count on you to:

• Analyse raw video and motion-capture data so we can pinpoint the most engaging sequences to animate.
• Develop custom algorithms that automate character rigging, lip-sync, and scene transitions, feeding those outputs directly into our animation software (Blender and After Effects).
• Optimise and document the entire workflow so our creative team can reproduce results without heavy technical hand-holding.

I’ll provide the datasets, style guidelines, and a shared Git repo; you bring reproducible code, clear comments, and model checkpoints ready for review. Once your contributions plug seamlessly into the animation pipeline and the test renders pass quality checks, the job’s done.

If collaborating on an AI-driven instructional video excites you, let’s talk timelines and milestones.

Skills: Python, CUDA, Machine Learning (ML), C++ Programming, Data Science, OpenCV, Data Analysis, Computer Vision

PROJECT CONTEXT

We are building a Computer Vision system for video analysis. We need to hire 2 profiles:
1. ARCHITECT (technical design, decisions, oversight)
2. DEVELOPER (implementation, coding, optimization)

This is a 6-8 week MVP project to build the FOUNDATION of our system (foundation + basic detection/tracking).

After Phase 1 validation, we may extend with future phases.

CRITICAL POINT

This project CANNOT be solved with:
- LLM (ChatGPT, Claude, Gemini)
- Generic vision APIs (Google Cloud, Azure)
- Low-code solutions or templates
- "Quick solutions"

This project REQUIRES:
- Real expertise in classical Computer Vision
- Deep Learning (PyTorch or TensorFlow)
- Proven experience: object detection + video tracking
- GPU optimization (NVIDIA CUDA)
- Production-grade code

TECHNICAL ARCHITECTURE

MVP Phase 1 = 2 main components:

1. VIDEO PIPELINE FOUNDATION
• Optimized video-to-frames decomposition
• Robust extraction and preprocessing
• Memory management for video streams
• Stack: OpenCV, FFmpeg, NumPy

2. DETECTION + TRACKING INTEGRATION
• YOLO v8+ for object/person detection
• DeepSORT for temporal tracking
• Frame-to-frame ID association
• Real-world condition reliability
• Stack: YOLO (Ultralytics), DeepSORT, PyTorch

MVP PHASE 1 TIMELINE

DURATION: 6-8 weeks total

WEEK 1-2: Architecture & Setup
- System design and technical decisions
- Development environment setup
- Testing framework design
- Performance benchmarking plan

WEEK 3-4: Video Pipeline
- Frame extraction pipeline
- Preprocessing and optimization
- Performance tests

WEEK 5-6: Detection + Tracking
- YOLO integration
- DeepSORT implementation
- ID management and stability

WEEK 7-8: Integration & Polish
- End-to-end testing
- Performance optimization
- Documentation and handoff
- Code cleanup and tests

DELIVERABLE: Working MVP with clean code + documentation

TECHNICAL STACK

Languages:
- Python 3.9+ (mandatory)
- C++ (optional, optimization)

Deep Learning & CV:
- PyTorch (preferred) or TensorFlow
- Ultralytics YOLO
- DeepSORT
- OpenCV, NumPy, scikit-image

Infrastructure:
- NVIDIA CUDA + cuDNN
- GPU memory optimization
- Docker (containerization)
- Git (version control)

WE'RE LOOKING FOR 2 PROFILES

PROFILE 1: ARCHITECT
- 5+ years Computer Vision experience
- Experience designing CV systems from scratch
- Strong understanding of YOLO, tracking algorithms
- Can make technical trade-off decisions
- Proposes optimizations and alternatives
- Oversees code quality and architecture
- Part-time or full-time OK (oversight role)

PROFILE 2: DEVELOPER (Senior)
- 3+ years production Computer Vision experience
- Expert in YOLO, OpenCV, PyTorch
- Experience with DeepSORT or similar tracking
- Strong Python + GPU optimization skills
- Can write clean, tested, production code
- Follows architectural decisions
- Full-time commitment preferred for 6-8 weeks

APPLICATION INSTRUCTIONS

Specify which role you're applying for: ARCHITECT or DEVELOPER

1. PORTFOLIO (mandatory)
- 2-3 CV projects you've delivered
- GitHub repos OR description + results
- Technologies used, your exact role

2. EXPERIENCE
- Years in Computer Vision (total)
- YOLO / object detection (versions)
- Tracking experience (DeepSORT, centroid, etc.)
- PyTorch/TensorFlow experience
- GPU optimization experience
- Production projects (not just Kaggle)

3. TECHNICAL OPINION
- Feasibility of MVP in 6-8 weeks: realistic?
- Any concerns or risks?
- Your approach to Phase 1?

4. TEAM PREFERENCE
- Have you worked with an architect/developer pair before?
- Preference for sync or async communication?

EXPECTED DELIVERABLES

CODE:
- GitHub repo (private/shared)
- Clean, tested Python code
- Unit tests (pytest)
- Requirements.txt / poetry.lock
- Meaningful docstrings

DOCUMENTATION:
- Architecture README (with diagrams)
- Installation guide
- API / usage examples
- Performance benchmarks (FPS, memory)
- Known limitations

HANDOFF:
- Code review completed
- Setup verified on clean machine
- Performance validated

FAQ

Q: Can one person do both (architect + developer)?
A: Possible for strong senior, but better with 2 people. More progress, better oversight.

Q: What YOLO version?
A: Open. v8 good starting point, v10 or ByteTrack alternatives welcome if justified.

Q: After MVP, what happens?
A: We evaluate quality. Strong MVP = potential Phase 2-4 continuation.

Let's build something solid!

• Describe your recent experience with similar projects

I need a Universal ZRA Smart Invoice Connector.

The concept is to create a middleware platform called AfriTax Connect that sits between ERP/Accounting Systems and the ZRA Smart Invoice platform. ZRA integration is achieved through the Smart Invoice API and VSDC (Virtual Sales Data Controller) framework used for ERP integrations.

Please see attached requirements for your attention

We need an embedded-Linux/cellular-connectivity specialist to get a Quectel EC200U 4G module providing reliable internet to a Raspberry Pi 5 using USB and UART both. The work is remote via screen share - the hardware is already assembled and powered on our side.

Deliverables:

- Reliable internet on the Raspberry Pi 5 through the EC200U module (ECM or RNDIS - whichever proves stable on this hardware), verified with ping and a real file download.

- Auto-connect on boot - a startup script/service (systemd) that brings up the module's data call and obtains the host IP/route/DNS automatically when the Pi powers on. No manual steps. This is essential: the device runs unattended with no keyboard or screen attached.

- Auto-reconnect watchdog - a service that detects a dropped connection and re-establishes it without intervention. Field sites have intermittent cellular coverage, so the link will drop and must recover on its own.

- GPS / location readout from the module (only if the unit's GNSS variant supports it - to be confirmed at project start; if unsupported, this item is void) - enable GNSS and provide a simple, reliable way to read current latitude/longitude on the Pi (e.g., a script that outputs lat/long, or writes it to a file/local endpoint the rest of our software can read).

- Reusable setup runbook + all scripts/service files - clear written steps plus the scripts, so we can replicate this identical setup on additional units ourselves without re-hiring.

- Signal & connection status exposed locally - a script/endpoint reporting current signal strength (RSSI/RSRP) and connection state, so we can remotely diagnose why a deployed unit went offline. Valuable once we have a fleet of devices in the field.

- Data-usage counter - track cellular data consumed, since SIMs have caps/costs across many units.

After greetings,

We are looking for a skilled freelance Unreal Engine programmer to help us build a playable prototype / vertical slice for an original single-player puzzle game.

The project is a 2D game with 3D elements, built in Unreal Engine, preferably using Blueprints rather than heavy C++ coding. The goal of this prototype is to prove the main gameplay mechanic and create a playable build that can support future pitching to potential investors.

The selected talent will work from the design direction, references, sketches, gameplay notes, and selected assets we provide. Some placeholder or temporary assets may also be required where final assets are not yet available.

The body of work is expected to include:

Playable Prototype / Vertical Slice:
A functional prototype that clearly demonstrates the main puzzle mechanic, player interaction, controls, and overall game feel.
Unreal Engine Blueprint Implementation
The project should preferably be developed using Blueprints, with clean, organized, and understandable logic that can be reviewed and continued later if needed.

Mobile-Focused Design:
The prototype should be developed with mobile platforms in mind, targeting iOS and Android where possible. Touch controls and mobile usability should be considered from the start.

Core Gameplay Interaction:
The prototype should include point, click, and drag functionality suitable for a puzzle game experience.

Basic Menu and UI:
The work should include a basic start menu, simple in-game UI, and any essential feedback systems required to understand and test the gameplay.

Basic Animation and Presentation:
Basic animation implementation will be required where needed to communicate actions, interactions, puzzle feedback, and game feel.

Use of Provided and Placeholder Assets:
We will provide a combination of references, sketches, direction, and some assets. The programmer should also be comfortable using temporary placeholder assets where required to complete the prototype.

Clean Project Delivery
The final delivery must include the full Unreal Engine project files, organized folder structure, source files, and a playable test build where applicable.

Timeline and Communication
The project timeline is approximately 3 weeks, with 6 scheduled catch-up calls during the production period. The selected talent must be comfortable communicating through scheduled calls for project discussions, work reviews, feedback sessions, and agreement on next steps. Clear communication and availability for these planned reviews are important for this role.

The current budget is €200, negotiable depending on experience, proposed scope, and delivery approach. We are open to discussing a realistic prototype scope that fits within this budget.

Revisions and Feedback
We would like to allow for up to three rounds of revisions, if required. Feedback may be provided through messages, annotated notes, and scheduled calls.

Experience with Unreal Engine, Blueprint scripting, mobile game prototyping, puzzle games, and low-budget indie game development is strongly preferred.

Please include examples of previous Unreal Engine prototypes, Blueprint systems, puzzle mechanics, mobile builds, or playable demos you have worked on. Applications with relevant portfolio links or short gameplay videos will be prioritized.

Applicants should also be comfortable joining scheduled calls for discussions, progress reviews, and feedback throughout the project.

An NDA agreement, license to edit, full ownership of the delivered project files, and license for commercial use of the work produced are required. The terms are considered accepted by the talent upon accepting the job offer.

Happy to answer any further queries over messages or a call for clarity.

Thank you.

We are looking to build a bot that can keep our telegram groups updated with members that are active under our broker inside our gold trading community

I’m building a small proof-of-concept that listens to an audio file and tells me how it feels. The focus is purely on analysis, not generation or recommendation. What I need is a working mood-detection pipeline that can ingest common formats (MP3, WAV, FLAC), extract the relevant features, and return an accurate emotional label for each track.

I’m open to either classical audio-signal processing combined with machine-learning classifiers, or a deep-learning approach built on libraries such as Librosa, PyTorch or TensorFlow—whichever you feel delivers the best accuracy without excessive latency. Please train or fine-tune your model on a dataset large enough to generalise across genres, then expose the result through a simple Python function or lightweight API endpoint.

Deliverable: fully commented source code, a short README explaining setup and usage, and a brief report on model performance (accuracy, key metrics, and any limitations you observed).

Skills: C Programming, Python, Software Architecture, Machine Learning (ML), C++ Programming, Audio Processing, Deep Learning, Classification

Location: United States
Description
Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.

Skills: Python, C++ Programming, Rust, Deep Learning, AI Research, AI Development

I need a robust Playwright-based automation framework written in C# that follows the opus oe sonet model from Claude and embraces a full BDD workflow. The framework must suit my “Automation framework” target rather than being tied to just one platform, so while web support is the priority, I want the architecture to stay open for possible mobile or desktop extensions.

The main focus is on end-to-end automation test coverage, yet the code structure should remain flexible enough that future performance or security layers could drop in without a rewrite. All test logic will live in readable .feature files, with step definitions, hooks, and a central object repository generated automatically.

Key deliverables
• Framework source in C# (.NET 6 or later) integrating Playwright
• CLI or UI utility that scaffolds new .feature files, page objects, hooks, and trace configuration
• Self-healing element mechanism: when a locator breaks, the framework must search alternative attributes and update the repository automatically, logging the change
• Consolidated execution report in HTML (pass/fail stats, screenshots, Playwright traces) produced at run-time
• Sample feature set that demonstrates login, search, and a negative path scenario
• README explaining setup, execution, and how to extend keywords, data sets, and hooks

Acceptance criteria
1. Running `dotnet test` against the sample suite executes headless and headed runs with Playwright, creates a fresh report, and stores traces.
2. Breaking a locator in the sample page object triggers the self-healing logic and the test still passes, with the update reflected in the repository file.
3. A contributor can generate a new scenario with one command, receiving stubbed steps, page class, and hook template ready for editing.

Use any auxiliary libraries you need (e.g., SpecFlow for BDD, FluentAssertions for checks, Allure or ReportUnit for reports) as long as licensing stays permissive. Keep the code lightweight, well-commented, and immediately runnable after a `dotnet restore`.

Deliver everything in a Git repository so I can review commits, run the suite locally, and integrate it into my pipeline.

Skills: .NET, C# Programming, Software Architecture, Software Testing, Test Automation, C++ Programming, Continuous Integration, Automation

I'm looking for an experienced TradingView developer to create a custom momentum indicator, specifically a modified Bollinger Bands. The customization needed is to combine it with other indicators.

Ideal skills and experience:
- Proficiency in Pine Script
- Experience with TradingView
- Knowledge of Bollinger Bands and other technical indicators
- Ability to customize indicators based on user requirements
- Strong attention to detail and problem-solving skills

Please include relevant examples of past work in your bids.

Skills: C Programming, Software Architecture, Metatrader, C++ Programming, Financial Analysis, Data Visualization, Pine Script, Market Analysis

I need a concise yet clear live demonstration that introduces reinforcement learning through a Q&A-driven format. During the session you will walk through a working example—feel free to use Python, OpenAI Gym, or any comparable toolkit—and answer a short set of practical-application questions I’ll provide in advance.

Alongside the demo, complete a small written assignment that summarises the example, explains the key decisions you made, and responds to those same practical-application questions in text form (about one page is enough).

Deliverables
• Live demo link or recording (10-15 min)
• Source code/notebook used in the demo
• Written assignment (≈1 page) covering the Q&A

Keep the material beginner-friendly, focused on showing how reinforcement learning works in practice rather than delving into every algorithmic detail.

Skills: JavaScript, Python, Software Architecture, Machine Learning (ML), C++ Programming, Artificial Intelligence, Deep Learning, Reinforcement Learning

I need a compact bot that connects directly to my Kotak Neo and Upstox accounts, tracks my running profit-and-loss in real time, and enforces a strict loss cap. The moment the preset threshold is breached the bot must refuse every new order and immediately square off every open position, then remain locked until I reset it.

To make that happen you’ll need to:

• Wire up to both brokers’ REST/WebSocket endpoints, authenticate with the keys I provide, and stream positions tick-by-tick.
• Maintain a live P/L calculation with sub-second latency and airtight error handling so a network blip doesn’t let an order slip through.
• Offer a simple way—env file, YAML or lightweight GUI—for me to change the loss limit on the fly.
• Log each decision (limit reached, orders blocked, positions closed) for audit purposes and future tuning.

I prefer Python for its solid async and broker-SDK support, but if you have a faster or more reliable stack in mind I’m open. Deliverables are the full, well-commented source, setup instructions, and a short screen recording that shows the bot hitting the loss cap, shutting everything down, and flatlining order flow.

I’ll accept the project once I can spin the script up on my VPS, see the live P/L updates, hit the loss limit in a paper-trade environment, and watch the automatic rejection and closure fire flawlessly. If you’ve already wrestled with Indian broker APIs or built risk-management safety nets, you’ll find this job straightforward.

Skills: PHP, Python, Software Architecture, C++ Programming, Software Development, API Development, REST API, Financial APIs

We’re looking for a technical content creator to produce coding walkthrough videos for dvl, an AI-assisted product engineering training platform.

You do not need to solve every problem from memory. You are encouraged to use AI tools such as ChatGPT, Claude, Cursor, GitHub Copilot, or other coding assistants.

Your job is to:

* Complete coding problems
* Verify the solution works
* Understand the reasoning
* Record your screen
* Create a professional walkthrough video

This is an ongoing role with multiple videos per week.

⸻

What You’ll Do

For each assignment:

1. Open the problem inside the dvl IDE
2. Solve the problem using any AI tools you’d like
3. Verify all tests pass
4. Write a short explanation of the solution
5. Record your screen while walking through the solution
6. Generate a voiceover using ElevenLabs
7. Edit the final video

Videos are typically 5–15 minutes long.

⸻

Tools You’ll Use

* Develow IDE
* Cursor or VS Code
* ChatGPT / Claude / AI coding tools
* ElevenLabs
* Screen recording software
* Video editing software

⸻

Ideal Candidate

You do not need to be a senior engineer.

We’re looking for someone who:

* Can understand basic software engineering concepts
* Is comfortable using AI coding tools
* Can explain technical ideas clearly
* Has experience creating videos or tutorials
* Has good written English

Bonus if you have experience with:

* React
* TypeScript
* Node.js
* Python
* Full-stack development
* Technical YouTube content

⸻

Example Problems

* Fix a React bug
* Implement a shopping cart feature
* Debug an API endpoint
* Add filtering to a data table
* Fix a database query
* Improve application performance

⸻

Deliverables

For each video:

* Completed solution
* Screen recording
* Voiceover
* Edited MP4 file
* Source files

⸻

To Apply

Please answer the following:

1. What AI coding tools do you use most often?
2. Have you used Cursor before?
3. Have you created tutorial or educational videos?
4. Share any examples of your work.
5. What is your hourly rate?
6. Record a short Loom video explaining how you would solve and teach a simple coding problem using AI.

⸻

Compensation

* Ongoing work
* Multiple videos per week
* Flexible hours
* Long-term opportunity for the right candidate

⸻

About dvl

Dvl is building the next generation of product engineering interview preparation. Users solve real-world full-stack engineering problems inside a desktop IDE with AI assistance, automated testing, and guided learning paths designed to help them become job-ready product engineers.

We are seeking an expert Embedded Systems Engineer to design a highly integrated, custom RTK GNSS rover board. You will be working from a proprietary reference architecture. The objective is to develop a 100% reproducible, multi-layer hardware design alongside a clean, custom open-source software stack.

Core Subsystems (High-Level)
Main Compute: ARM-based SoC (Requires custom Embedded Linux BSP/OS)

Positioning: High-precision, multi-frequency RTK GNSS module

Network: 4G LTE Cellular module (for continuous NTRIP corrections)

Local Radio: UHF Transceiver (400MHz band)

Sensor Fusion: 6/9-axis IMU (for tilt compensation)

Wireless: Standard Wi-Fi/Bluetooth module

Key Responsibilities
Hardware Design: Create schematics and route a complex multi-layer PCB (likely 6–8 layers) in Altium or KiCad. You must have extensive experience with strict RF signal integrity, shield design, and impedance matching to manage co-existence between four simultaneous RF pathways (GNSS, LTE, UHF, Wi-Fi).

Firmware/OS Development: Build a lightweight, custom Embedded Linux distribution (e.g., Yocto or Buildroot) tailored for the main SoC. Write the core orchestration application to parse positional data, inject RTCM corrections from the network/radio, and process IMU orientation streams.

Deliverables
Production-ready manufacturing files (Gerbers, BOM, and CPL/Centroid files).

Fully documented, custom Linux BSP and application source code.

Remote hardware bring-up and debugging support for the initial prototype batch.

Seeking senior JUCE expert to join our small plugin development team. We have 20k active users and really unique products.

The work is very architecture oriented and involves solving technical plugin challenges. Must have C++ and JUCE mastery. Must have shipped AU / AAX / VST and experience handling the quirks of each format.

This is not a DSP type of role.

Tôi cần một chuyên gia viết nội dung để tạo các mô tả sản phẩm thời trang hấp dẫn, ngắn gọn và đúng tông thương hiệu. Công việc bao gồm:

• Nghiên cứu nhanh đặc điểm sản phẩm (chất liệu, kiểu dáng, kích cỡ, ưu điểm) dựa trên ảnh hoặc thông tin tôi cung cấp.
• Viết mô tả sản phẩm chuẩn nội dung thương mại: câu mở thu hút, phần mô tả chi tiết, và lời kêu gọi hành động.
• Đảm bảo nội dung dễ đọc, không lỗi chính tả, tối ưu SEO cơ bản với từ khóa tôi sẽ gửi kèm.
• Giao file ở định dạng Word hoặc Google Docs, sẵn sàng để tôi sao chép lên website.

Tôi ưu tiên người từng viết mô tả cho quần áo, phụ kiện hoặc các sản phẩm fashion tương tự. Vui lòng gửi một-hai đoạn mẫu bạn đã viết để tôi đánh giá nhanh trước khi bắt đầu.

Skills: C Programming, Graphic Design, Copywriting, SEO, C# Programming, C++ Programming, Content Writing, Fashion Writing

I’m looking for an experienced developer who can build fully emulated firmware for a DMA card. The firmware should be compatible with Windows and capable of emulating several key functionalities, including:

100% CFG
The configuration space of the firmware should perfectly replicate that of a legitimate device, allowing it to be detected and recognized by the system as authentic hardware.

BAR Support
BAR (Base Address Register) represents the memory region inside a PCIe device. The BIOS reads this information in order to properly communicate and interact with the device.

Emulation
Correct BAR handling ensures that when a driver sends a request to the PCIe device’s BAR, the firmware responds with the appropriate data, effectively imitating the behavior of a real device.

Full Emulation
Complete emulation includes accurate responses to MSIX and MSI messages, support for I/O space, and interrupt messaging, ensuring full compatibility with the operating system and system expectations.

DRV Scan
Must return a “green” status when checked with the DRVScan Tool.

Additionally, the firmware should be able to operate alongside several anti-cheat systems, including:

EAC (Easy Anti-Cheat)

VGK (Vanguard)

FACEIT Anti-Cheat

The firmware must also include full BAR support.

The ideal candidate should have strong experience in firmware development, solid knowledge of DMA card architecture, and familiarity with the listed anti-cheat systems.

Skills: C Programming, C++ Programming, Debugging, Software Development, FPGA, Embedded Systems, PCI Express, Security, DDR3 (PCIe, board design/fpga), Reverse Engineering

WHAT WE'RE SEEKING
We are seeking a skilled developer to build an offline, real-time assessment system that analyses a user through webcam and microphone input.
The system should assess visible communication signals such as posture, gaze/head position, facial cues, hand movement, body movement, and voice delivery cues such as pitch, pace, pauses, volume, and intonation.
This is not a cartoon avatar, game character, VR experience, or VFX project. The core deliverable is the local assessment engine. The realistic human-facing interface is a separate presentation layer and should be implemented using the simplest practical method that meets the agreed requirements.

THE MISSION
Build a local computer vision and voice analysis system that processes live webcam and microphone input in real time, converts those signals into assessment-ready features, applies configurable assessment logic, and produces real-time feedback through a realistic human-facing interface.
The human-facing interface may use pre-recorded human video states, a lightweight talking-head interface, a voice-led coach interface, visual overlays, or another local method proposed by the developer.
All execution must run locally. No cloud inference, telemetry, analytics, external callouts, or subscription runtime dependencies are permitted.

TARGET DEVICE
Primary target: Windows 11 consumer hardware.
Must be benchmarked on the agreed target machine.
GPU acceleration may be used where appropriate.
Must not require non-consumer cluster GPUs.
Kinect, depth cameras, or specialist hardware may be proposed only as optional enhancements, not default requirements.

IN SCOPE

- Real-time webcam capture.
- Real-time microphone capture.
- Webcam-based pose estimation / body landmark tracking.
- Face landmark detection.
- Hand landmark tracking where practical.
- Gaze or head-pose estimation where practical.
- Voice feature extraction, including pitch, pace, pauses, volume, energy, and intonation features.
- Feature extraction layer that converts raw landmarks/audio into assessment signals.
- Configurable assessment logic using local JSON/YAML-style configuration.
- Hot reload for assessment logic without restarting the application.
- Real-time feedback events based on the assessment logic.
- Realistic human-facing interface layer.
- Visual debug overlay showing extracted landmarks/features during development and demo.
- Local benchmarking of latency, FPS, CPU/GPU usage, RAM usage, and sustained runtime.
- Offline verification showing no external calls.
- Clear separation between capture, feature extraction, assessment logic, scoring, feedback events, configuration, human interface, and application/UI layers.
- Documented interfaces between major components.
- Setup documentation, run commands, architecture notes, benchmark notes, and known limitations.

TECH STACK
Note: We will mutually agree on any tech stack changes to ensure no risk to target expectations and success factors:
* Visual engine: Unreal Engine 5
* Human character: MetaHuman first; custom rig later only if needed
* Face/lip animation: NVIDIA Audio2Face-3D / ACE Unreal Plugin
* Body/gaze/gesture: Unreal animation state machine
* Real-time audio/session: LiveKit Agents
* Turn-taking: LiveKit turn detector + Silero VAD
* TTS: Benchmark Chatterbox Turbo
* Backend: Existing backend via clean event bridge
* UI: React Tauri 1.8 wrapper - AJ to do vs PYQT6
* External webcam: OBS Virtual Camera only if needed
MediaPipe : Local multi-modal framework that extracts face, iris, hand, and body pose landmarks concurrently using device hardware.​
ONNX Runtime (onnxruntime-gpu): High-performance local inference engine optimized for running .onnx models utilizing Windows CUDA or DirectML acceleration.​
OpenCV (opencv-python): Native computer vision library used for real-time webcam frame acquisition, image preprocessing, and drawing visual debug overlays.​
sounddevice: Thread-safe audio library interfacing with Windows WASAPI/ASIO drivers to stream raw microphone input into NumPy arrays.​
Silero VAD: Ultra-lightweight voice activity detection model running locally via ONNX to segment real-time speech and calculate pauses.​
parselmouth (Praat for Python): Local acoustic analysis library utilizing mathematical signal processing to extract fundamental frequency for pitch tracking.​
scipy.signal & numpy: Scientific computing libraries used to perform instantaneous local RMS calculations for real-time volume and energy tracking.​
opensmile: Standardized feature extraction framework optimized in C++ to capture comprehensive acoustic parameter sets completely offline.​
PyQt6 / PySide6: C++ backed GUI framework providing hardware-accelerated widgets (QMediaPlayer) and thread-safe signaling to drive the presentation layer.​
watchdog: Local file monitoring utility that actively monitors file changes and triggers instantaneous hot-reloads of configuration files.​
psutil: System monitoring tool that queries the local OS kernel to benchmark CPU, RAM, and application process utilization.​
pynvml: Direct local wrapper for the NVIDIA Management Library used to programmatically log real-time GPU and VRAM metrics.

CLIENT TECHNICAL ENVIRONMENT:
* RTX 4080 15GB VRAM
* Ryzen 9 4950H
* 32GB RAM

PROCESSES (to be refined):
- User Experience During Session
app launch -- zoom like experience (see image)

- Post Session
User stats evaluation summary (driven by all of the info captured within this project): BPS, Pros, Cons, Body Language

Settings menu (icon) -
- Content : Load data (subject matter for user to discuss) - Rules config
- Presenter Persona : System Prompt
- LLM: Choose Ollama Model from drop-down list. User can download local models. Show local models downloaded. Can be deleted. Include synch button to fetch latest models/changes.



OUT OF SCOPE
- Cloud computer vision APIs.
- Cloud speech or voice analysis APIs.
- Subscription-based runtime dependencies.
- Telemetry, analytics, or external callouts.
- Enterprise production-grade deployment.
- Full 3D character pipeline unless separately approved.
- Skeletal mesh / rigged character development unless separately approved. (no only head, shoulder, arms only)
- VFX-heavy digital human rendering unless separately approved.
- Kinect or depth-camera dependency as a default requirement. (going into the distance)
- Deepfake-style synthesis unless explicitly approved in writing.
- Multilingual translation.
- Audio transcription beyond what is required for direct voice delivery analysis.
- Emotion recognition claims unless legally, technically, and contractually approved.
- Hardcoded assessment rules where configuration is practical.

IDEAL EXPERIENCE
Computer Vision
- Real-time pose estimation.
- Body landmark / skeletal landmark tracking.
- Face landmark detection.
- Hand tracking.
- Head-pose or gaze-related estimation.
- OpenCV, MediaPipe, ONNX Runtime, PyTorch, TensorRT, or equivalent local tooling.

Audio / Voice Analysis
- Real-time microphone handling.
- Pitch, tempo, pause, volume, energy, and intonation feature extraction.
- Local DSP/audio feature pipelines.
ffmpeg, PyAudio, sounddevice, librosa, torchaudio, or equivalent tooling.

Local ML / Runtime Optimisation
- Running models locally on consumer hardware.
- Optimising for latency and memory usage.
- Practical benchmarking and profiling.
- ONNX, PyTorch, TensorRT, or equivalent runtime choices.

Human Interface
- Video-based human presenter interfaces.
- Lightweight talking-head interfaces.
- Voice-led coaching interfaces.
- Real-time feedback UI.
- Ability to keep the presentation layer separate from the assessment engine.

Architecture
- Clean modular design.
- Testable component boundaries.
- Configuration-driven behaviour.
- Clear handover documentation.
- Practical trade-off decisions.
- Low technical debt MVP delivery.

NON-NEGOTIABLES
Offline Operation
- The system must run locally.
- No required internet connection.
- No telemetry.
- No analytics.
- No subscription runtime dependency.

Performance
- Target end-to-end feedback latency: under 100ms where technically practical.
- Candidate must benchmark actual latency on the agreed hardware.
- Candidate must benchmark memory usage and sustained runtime.
- Candidate must identify any parts that cannot realistically meet the target and explain why.

Architecture Quality
- The assessment engine and human-facing interface must be separate.
- Webcam capture, audio capture, feature extraction, assessment logic, configuration, feedback events, and presentation must not be tightly coupled.
- Assessment rules must be configurable where practical.
- The MVP must be maintainable, modular, and suitable for clean handover.

Communication
- Explain technical decisions clearly. - at least 30min video catch up, everyother day.
- Flag unclear requirements early.
- Flag delivery risks at least one day before they affect delivery.
- Shared-screen review sessions may be required.
- Live walkthroughs of architecture, benchmarks, and code may be required.
- Mutually agree any changes before committing

Output Quality
- AI-assisted coding is permitted up to a maximum of 60%.
- The developer remains responsible for all code quality.
- Code must be lean, modular, testable, and documented.
- No unsupported implementation choices.
- No unnecessary complexity.
- No hidden dependencies.

Handover
- Hand over all source code, assets, configuration files, setup notes, benchmark results, and documentation.
- Provide clear run instructions.
- Provide dependency and licensing notes.
- Provide known limitations.
- Remove project files and assets from supplier infrastructure after handover unless written approval is given.

DEFINITION OF DONE
The project is complete when:
- The application runs locally on the agreed Windows 11 hardware.
- Webcam and microphone input are captured and processed in real time.
- The system extracts pose/body landmarks, face landmarks, and agreed voice delivery features.
- The system extracts hand, gaze/head-pose, or equivalent visible communication features where technically practical.
- The system converts raw landmarks and audio features into assessment-ready signals.
- The system applies configurable local assessment logic.
Configuration changes can be hot reloaded without restarting the application.
- The system produces real-time feedback events. (BPS, body language, eye-tracking)
- The feedback events drive the agreed human-facing interface.
- The human-facing interface is separate from the assessment engine.
- The system includes a visual debug mode showing key extracted landmarks/features.
- Offline testing confirms no network calls (with exception of ollama cloud and initial system install), telemetry, analytics, or cloud dependencies.
- Source code is modular and documented.
- Handover package is complete.

ACCEPTANCE CRITERIA
- Live Demo
- Demonstrates webcam and microphone input being processed in real time.
- Shows extracted body/pose, face, and voice features.
- Shows real-time feedback being generated.
- Shows feedback driving the agreed human-facing interface.
- Configuration Demo
- Assessment logic is stored in local configuration files.
- A configuration value is changed during the demo.
- The system applies the changed logic without application restart.
- Offline Evidence
- Demo runs with network disabled.
- Logs or monitoring evidence show no external calls.
- No telemetry or analytics are present.
- Benchmark Evidence
- Benchmark report includes hardware used, model/runtime choices, FPS, latency, CPU/GPU usage, RAM usage, and sustained runtime.
- Any missed performance target is explained with evidence and mitigation options.
- Architecture Evidence
- Code review confirms separation between capture, feature extraction, assessment logic, configuration, feedback events, human interface, and application/UI layers.
- Interfaces between major components are documented.
- Architecture notes identify key trade-offs and known limitations.
- Source code, assets, configuration files, setup instructions, run commands, benchmark results, and known limitations are provided.
- Supplier confirms deletion of retained project materials unless written approval is given

PAYMENT CONDITIONS
* I’ll only accept work that meets the agreed standards. These will not change from what we've discussed

INVOICING
* Invoice like this please per week:
25hrs x 24.61 = 615GBP

Coding standards:
* Must have a clear and true seperation of concerns between FE and BE
* This means the front and backend are completely seperate and connected only by an integration layer.
* You can make superficial changes to the front layer, with zero risk to the backend.
* All files must be under 600 lines long inclusive of comments and single purpose. Only exception are shared utilities
* If a file exceeds 600 lines, then consider that it's either inefficient/bloated, or is doing more that one thing
* Examples of sinlge purpose: One file is for LLM integration, one file for feature x, another file for feature y (and so on)
* All code must include comments within files (applies only where possible, since you cannot add comments to some files due to syntax issues ). This includes:
* Before imports: file name with path + points on the unique features of the file
* Comments throughout code to explain what is dynamic such that any idiot like me can understand the code
* Ensure code is dynamic and flexible - not rigid, fragile or with hardcoded values .