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I’m looking for someone who can help me create a super realistic, low-cost way to produce many UGC-style ecommerce ad videos.

The ideal deliverable is a workflow I can install and run on my own local computer or low-cost server. It should be able to generate video variations in the background using product images, scripts, hooks, voiceovers, and simple creative briefs.

However, I’m also open to working with someone who can personally help me generate the videos, as long as the workflow is cheap, scalable, and repeatable, not based mainly on expensive paid platforms.

This is for ecommerce ads, so the output needs to feel like real UGC: natural, realistic, mobile-first, and suitable for Meta/TikTok style creatives.

What I Need

I want either:

Option A: Build me the workflow

A local or very low-cost installable pipeline I can run myself.

Or:

Option B: Help me generate videos

You use your own efficient workflow to help me produce lots of UGC-style videos at low cost.

In both cases, the goal is the same:
create many realistic UGC video ads cheaply and repeatedly.

The Workflow Should Ideally Support
Product image input
Script/hook input
Voiceover generation or uploaded voiceover
AI-generated lifestyle/product video clips
Talking-head or UGC-style clips if possible
Captions and text overlays
9:16 vertical video output
Batch generation in the background
Multiple creative variations from one product
Clear cost per finished video
Important

Please do not apply if your solution is just using expensive paid platforms like HeyGen, Arcads, Runway, Kling, Higgsfield, etc.

Those can be used as references, but I’m looking for a workflow that is mostly:

Local
Open-source
Automated
Cheap per video
Scalable for many creatives
Deliverables

Depending on your approach, deliverables can include:

Working local/installable workflow
ComfyUI or similar workflow
Python/FFmpeg automation
Recommended local AI models and tools
Batch generation system
Setup instructions
Cost breakdown per video
2–3 sample UGC-style videos
Documentation or screen recording
Or ongoing generation of UGC videos using your low-cost workflow
Ideal Candidate

You should understand:

Local AI video generation
ComfyUI or similar workflows
Stable Diffusion / Flux / Wan / Hunyuan / AnimateDiff or similar
AI image-to-video workflows
Voiceover, captions, and editing automation
Ecommerce ads and UGC-style creatives
How to make AI output look realistic, not obviously AI-generated
Screening Question

Start your proposal with CHEAP UGC PIPELINE.

Then answer:

What is the cheapest realistic workflow you would use to create lots of UGC-style ecommerce videos, and would you build it for me to run locally or help me generate the videos yourself?

Also include:

Estimated cost per finished video
Required hardware or server setup
Example tools/models you would use
Any examples of similar work

I am expanding an internal application that monitors the health of industrial gas turbines and now needs a robust predictive-maintenance module. The current environment streams high-resolution sensor feeds in JSON and is backed by several years of curated historical performance data. The goal is to turn those two sources into accurate failure-risk forecasts and actionable maintenance recommendations.

You will design and implement the full workflow—data ingestion, cleansing, feature engineering, model training, and deployment—inside a Python-based stack (pandas, scikit-learn or similar; feel free to propose alternatives such as PySpark or TensorFlow if they offer clear advantages). Real-time scoring must run fast enough to support control-room dashboards, and the results should be exposed through an API the rest of the system can call.

Key deliverables
• Data pipeline that pulls JSON sensor streams and historical records into a unified store
• Predictive models with documented performance metrics (precision, recall, ROC-AUC)
• Automated retraining script tied to new data drops
• REST endpoint (or MQTT topic) that returns health indices and recommended maintenance windows
• Concise technical documentation so our engineers can maintain and extend the code

Acceptance criteria
– Model accuracy equal to or better than the current rule-based alarms by at least 20 %
– End-to-end latency under 5 s for a single turbine data packet
– Code and docs delivered via a Git repository and a short hand-off call

Environmental data is not in scope right now, but the architecture should stay flexible enough to add it later. Let me know which libraries or cloud services you prefer so we can align on the tech stack before kickoff.

Skills: Java, JavaScript, Python, Software Architecture, Machine Learning (ML), Data Science, API, Pandas

OVERVIEW

I'm looking for an experienced n8n developer to build a multi-workflow AI automation system for my account management team. The system uses Claude (Anthropic AI) to automatically read inbound emails, pull job data from ServiceM8, draft contextual replies in Front App, and build quotes in Quotient — with account managers reviewing and approving before anything is sent.
This is a well-scoped project with a clear technical brief ready to hand over on day one.
PLATFORMS INVOLVED

Front App — customer email hub (inbound trigger + draft replies + internal comments)
ServiceM8 — field service platform (client lookup, job history, notes, photos)
Quotient App — quoting platform (template matching + custom quote building)
Anthropic API (Claude AI) — email reading, reply writing, action items, quote content
n8n — workflow orchestration connecting all of the above
THE THREE WORKFLOWS TO BUILD

1
Work Order Email Received
→
New work order email arrives in Front App
→
Claude extracts client name, address, and job type from the email
→
ServiceM8 queried to find the client and pull full job history
→
Internal comment posted in Front with the history summary
→
Claude drafts a relevant reply referencing the job and prior history
→
Draft saved in Front for account manager to review and send
2
Progress Update Email Received
→
Progress update email arrives in Front App
→
Claude identifies it as a progress update and extracts job details
→
Current job status pulled live from ServiceM8
→
Claude drafts a precise reply using real job status data
→
Draft saved in Front for account manager to review and send
3
Tradesman Attends Job (most complex)
→
Job marked as attended in ServiceM8 — webhook trigger fires
→
Tradesman notes and photos retrieved from ServiceM8
→
Original Front thread identified and matched to the job
→
Claude drafts a post-visit summary email with photos attached
→
Claude generates action items for account manager (posted as internal comment)
→
Claude reads notes, matches to Quotient templates where possible, writes custom line items where needed
→
Quote built in Quotient and saved in draft for account manager review
KEY REQUIREMENTS

Nothing is sent automatically — all emails and quotes require account manager approval
Quotes saved in draft/review state in Quotient
Graceful error handling: client not found, no photos, no template match, API timeout
Tradesman notes are informal/unstructured — Claude prompts must handle this robustly
All workflows built and tested in n8n (Cloud preferred to start)
IDEAL CANDIDATE

Strong n8n experience with complex multi-step workflows
Comfortable with REST API integrations (Front, ServiceM8, Quotient)
Experience calling AI APIs (Anthropic/OpenAI) from n8n
Able to craft effective Claude system prompts
Clear communicator — I want to understand what's being built as we go
CREDENTIALS I WILL PROVIDE

Front App API key + Inbox IDs
ServiceM8 API key
Quotient API key + full quote template list
Anthropic API key
n8n Cloud access
To Apply — Please Include:

Your experience with n8n and any similar automation projects
Have you worked with Front App or ServiceM8 APIs before?
Your estimated timeline and rough cost breakdown per workflow
Any questions about the brief
Full technical brief available immediately upon engagement.

We are seeking an AI developer with expertise in computer vision to enhance our operations in the mining, manufacturing, and oil & gas industries. The role involves developing and implementing AI solutions to improve efficiency and accuracy. Experience with machine learning and large language models is essential. The ideal candidate will have a strong understanding of domain-specific challenges and be able to integrate AI solutions effectively.
Implement computer vision, analysing footage from harsh industrial environments. X-ray video footage to detect faults / equipment stress.

Experience and use cases in mining and oil and gas and manufacturing industry would be beneficial.

Building a solution for optimising mining, manufacturing and logistics process.

Time series data analysis and forecasts
LLMs - chat bots language models

• Do you have experience in applying AI in mining or oil and gas or manufacturing industries . Especially if you can demonstrate computer vision examples/portfolio .
• Describe your recent experience with similar projects

Hiring: Odoo Developer (Remote – Full-Time)

We are looking for a Full-Time Remote Odoo Developer with 2+ years of proven Odoo development experience to join our growing team.

Requirements
Minimum 2+ years of Odoo development experience (Mandatory)
Strong knowledge of Python, PostgreSQL, XML, JavaScript, HTML, and CSS
Experience in Odoo customization, module development, and integrations
Hands-on experience with both Odoo Community and Enterprise
Ability to develop custom modules, reports, workflows, and APIs
Experience with Sales, Purchase, Inventory, Accounting, Manufacturing, and HR modules is an advantage
Strong problem-solving and debugging skills
Good communication skills in English
Responsibilities
Develop and customize Odoo applications
Create and maintain custom modules
Integrate Odoo with third-party systems and APIs
Troubleshoot and resolve technical issues
Optimize system performance and code quality
Work closely with consultants and project managers
Prepare technical documentation
Employment Details
Position: Odoo Developer
Type: Full-Time
Location: Remote
Experience: Minimum 2+ years in Odoo Development
To Apply

Please send:

Updated CV
Odoo project portfolio
Years of Odoo experience
Expected salary
Availability

Responsibilities
- All work must be your own. Use of LLMs or other AI tools to generate, assist with, or complete tasks is strictly prohibited — this data is used to train and evaluate AI models, so AI-generated submissions defeat the purpose, are detectable, and are grounds for removal.
- Evaluate code samples from simulated LLM conversations — select the strongest option and clearly explain your reasoning.
- Curate and annotate code snippets for training data across tasks such as code generation from natural language, code completion/infilling, debugging and repair (using both natural-language and program context), and code translation, refactoring, summarization, and documentation.
- Perform quality assurance on peer-generated content to ensure it meets accuracy, clarity, and technical standards.


Requirements:

- Strong coding proficiency in one or more of: Go, Rust, C#, C++, Kotlin, or Ruby.
- Excellent written English, especially for explaining technical concepts clearly and concisely.
- Comfortable working in code editors, spreadsheets, and browser-based annotation/QA tools.

What you'll do:

Build automations connecting tools like Google Sheets, Gmail, Slack, and CRMs
Set up AI-powered workflows (data enrichment, email digests, auto-tagging, lead processing)
Work with platforms like Make, n8n, Zapier, or custom scripts (Apps Script, Python)
Integrate LLM APIs where useful

You should have:

Proven automation projects (share examples)
Comfort with APIs and at least one no-code/low-code platform
Clear communication and ability to work independently

To apply: Send 2-3 relevant examples and a one-line note on how you'd approach automating a daily sales-tracker email digest.

We are seeking an experienced Python Developer to build Marketplace and scale a multi-vendor platform. The ideal candidate should have strong experience with Python, Django or FastAPI, REST APIs, payment gateway integrations, user authentication, vendor management, order processing, and scalable backend architecture. Experience building marketplaces, SaaS platforms, or eCommerce solutions is highly preferred. You will be responsible for developing secure, high-performance features, optimizing system performance, and ensuring a seamless experience for vendors and customers. This is an opportunity to work on a long-term project with ongoing development and feature enhancements.

Hi. We're building an AI-powered coaching app that helps users interact with a personalized AI mentor. The system provides ongoing guidance, goal tracking, and tailored recommendations based on user behavior and history.

We’re looking for a full-stack developer or team who can help build the MVP and core AI experience, not just a chatbot, but a structured AI coach with memory and personalization.

What You'll Do

Build AI chat and voice-based coaching features using LLM APIs (OpenAI / Claude)
Implement user personalization, memory, and context handling
Develop onboarding flows to capture user goals and preferences
Create backend services for AI orchestration and user management
Design scalable API architecture for mobile app integration
Work on knowledge ingestion and retrieval for coaching content

Tech Stack (Preferred)
React Native or Flutter
Node.js, Java Spring Boot, or Python FastAPI
PostgreSQL, Redis
OpenAI / Anthropic APIs
AWS or GCP

Requirements
Strong full-stack development skills
Experience with LLM integration and conversational systems
Understanding of AI memory, RAG, or personalization systems
Mobile development experience (iOS/Android)

Nice to Have
Experience with AI agents or workflow systems
Voice AI / speech interfaces
Background in coaching, education, or productivity apps

Deliverables
Working AI coaching MVP (mobile app + backend)
User memory and personalization system
Documentation for future expansion

Please share examples of similar platforms you’ve built.

Everything for my Windows desktop application is already coded in Python; I simply need a fresh set of expert eyes to ensure the code is solid and to guide me through a smooth launch. Your role is to review the existing source, spot any lurking issues, suggest (and, with my approval, implement) quick fixes, then package the app so it installs and runs cleanly on recent Windows versions.

You are welcome to use your preferred tooling—PyInstaller, cx_Freeze or similar—and advise on best-practice signing and versioning. Once the build is stable, I’ll rely on you to walk me through a brief test run and hand over a distributable installer or executable, plus a concise change log of anything you touched. If you can have this all wrapped up promptly, let’s get started.

Skills: Python, Windows Desktop, Software Architecture, Software Testing, C++ Programming, Software Development, Application Packaging, Desktop Application

I need a precise, methodical review of the data held in our production databases to confirm every record is accurate. The assignment is limited to accuracy checks—completeness and consistency are out of scope—so I expect you to zero-in on incorrect values, mismatched formats, and any figures that fail to meet predefined business rules.

Here is what I’ll provide once we start: secure, read-only access to the database, a short data dictionary, and the list of critical tables and fields that drive our dashboards. Your task is to analyse those tables, flag inaccuracies, and deliver a concise report describing each issue, how you identified it (SQL, Python, BI tool, etc.), and a recommendation to fix or prevent it.

Acceptance criteria
• All critical fields scanned for accuracy issues
• A reproducible script or query set included
• A final summary report highlighting problems and recommended remediation steps

If you have strong SQL skills and experience validating large datasets, I’m ready to get this moving quickly.

Skills: Python, Data Processing, SQL, Database Administration, Database Programming, Data Cleansing, Data Analysis, Database Management

Associate Technical Program Manager

Employment Type: Full-time (40 hours/week)
Duration: Long-term / Permanent
Language Requirements: English (minimum B2 level), German is a plus
Interview Process: 2–3 interview rounds

About the Role
We are looking for a highly organized, detail-oriented, and proactive Associate Technical Program Manager to support the execution of critical technology and AI development initiatives.
In this role, you will work closely with cross-functional teams of Software Engineers, Data Engineers, and Machine Learning Engineers across Europe and Tunisia. You will help coordinate key technical workstreams, including data collection, AI model development, platform engineering, and deployment activities, ensuring alignment, transparency, and timely execution.
This is an excellent opportunity for someone who enjoys bringing structure to fast-moving technical environments and wants to contribute to the development of innovative AI solutions in healthcare and diagnostics.

Responsibilities
Program Coordination
Develop, maintain, and update project plans, timelines, sprint schedules, Gantt charts, and project documentation
Track progress across multiple technical workstreams and monitor activities against project milestones and critical paths
Identify risks, bottlenecks, and dependencies early and proactively escalate blockers to leadership when necessary
Support project planning, resource coordination, and execution activities across engineering teams
Cross-Functional Alignment
Organize, coordinate, and facilitate technical meetings, including sprint planning sessions, daily stand-ups, retrospectives, and project reviews
Ensure alignment on priorities, deliverables, timelines, and next steps across technical and business stakeholders
Monitor cross-team dependencies and follow up on action items to ensure accountability and execution
Serve as a communication bridge between engineering teams and leadership

Reporting & Documentation
Prepare clear and concise status reports covering project progress, risks, milestones, and key decisions
Maintain project documentation, knowledge bases, technical requirements, and decision logs
Ensure project information remains accurate, accessible, and up to date
Promote consistent and high-quality documentation practices across engineering teams
Process Improvement
Support the implementation of lightweight and effective project management processes
Assist with KPI tracking, project reporting, and operational improvements
Help foster a collaborative, agile, transparent, and accountable team culture
Continuously identify opportunities to improve team efficiency and communication

Required Qualifications
2–5 years of experience in Project Coordination, Project Management, Program Management, Technical Program Support, or similar roles within software, technology, or AI-driven environments
Experience working with cross-functional engineering teams, including Software Engineering, Data Engineering, and Machine Learning teams
Basic understanding of software development workflows and modern engineering practices
Familiarity with:
Git and GitHub
Pull request and code review workflows
CI/CD processes
Cloud platforms such as AWS, GCP, or Azure
Experience supporting Agile development methodologies, including Scrum, Kanban, or hybrid frameworks
Hands-on experience facilitating:
Sprint planning
Daily stand-ups
Retrospectives
Project reviews

Proficiency with project management and collaboration tools such as:
Jira
Notion
Confluence
Similar project tracking platforms
Strong organizational skills with the ability to manage multiple priorities and track dependencies across projects
Excellent written and verbal communication skills in English
Ability to translate complex technical topics into clear and actionable updates for different audiences
Valid work authorization within the European Union or Switzerland

Preferred Qualifications
Familiarity with the AI and Machine Learning development lifecycle, including:
Data collection and curation
Model development and training
Validation and testing
Deployment and monitoring
Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, Business Informatics, or a related field
Basic Python skills for data analysis, automation, or workflow support
Experience working with distributed, remote, or multinational teams
Exposure to healthcare technology, diagnostics, medical devices, or regulated environments is a plus
Interest in emerging AI technologies and software development processes

⚠️ Important:

Candidates who attach a CV to their application will be prioritized.

• Are you in Berlin and would this be suitable for you (hybrid system; remote work possible after adaptation)?
• Describe your recent experience with similar projects

Need a developer to build a low-latency browser streaming solution. The project involves creating a system that can stream video from one laptop to another with minimal delay. The ideal candidate will have experience in peer-to-peer video streaming and be able to optimize for low latency. Familiarity with WebRTC and JavaScript is essential.

I have an Excel workbook that already contains a list of reference numbers. A separate PDF holds the source data in clear table form. I need a reliable way to look up each number from Excel inside that PDF and return the exact matches into a new summary sheet within the same workbook.

Here’s the flow I’m picturing:

• Read the tables in the PDF (there are no scattered values—everything sits neatly in rows and columns).
• Compare every number in my existing Excel list against those PDF tables.
• Write the matched results, side-by-side with their source row information, into a dedicated “Match Summary” sheet so I can filter or pivot them later.

I’m open to VBA, Power Query, Python with openpyxl/tabula-py, or other practical methods—as long as the solution is repeatable when the files are updated. Accuracy is critical; false positives or missed matches defeat the purpose. If you’ve built similar Excel-to-PDF matching tools, let me see a short demo or outline of your approach when you bid.

Deliverable: a working Excel file (plus any linked script) that, on one click, refreshes the Match Summary sheet with the latest corresponding numbers pulled from the PDF tables.

Skills: Visual Basic, Excel, Statistics, Statistical Analysis, Excel VBA

I will provide a corpus of raw call recordings, each in MP3 format, and I need a machine-learning model that can automatically flag fraudulent activity. The model must correctly recognise the three problem categories—Phishing, Robocalls and Telemarketing scams—without human intervention.

What I expect you to handle:
• Pre-processing: clean the audio and extract features (e.g., MFCCs or spectrograms) that capture speaker and content cues.
• Modelling: design, train and fine-tune a classifier; CNN, RNN, Transformer or a hybrid approach is acceptable if it improves accuracy.
• Evaluation: deliver precision, recall, F1 and a full confusion matrix for each fraud type so I can judge real-world performance.
• Deployment assets: an inference script or small REST service that accepts an MP3 file and returns the predicted class with a confidence score, plus all model weights and code (Python with TensorFlow or PyTorch preferred).

Please outline any similar speech analytics projects you have completed and the toolkit you would like to use. Once we agree on architecture and milestones, I can release the audio so you can get started right away.

Skills: Python, Algorithm, Machine Learning (ML), Big Data Sales, Audio Processing, Deep Learning, Convolutional Neural Network, Recurrent Neural Network

Data Engineer (ML Platform & MLOps)

Employment Type: Full-time (40 hours/week)
Duration: Long-term / Permanent
Language Requirements: English (minimum B2 level), German is a plus
Interview Process: 2–3 interview rounds

About the Role
We are looking for an experienced Data Engineer to build and scale the core data, machine learning, and deployment infrastructure powering an innovative AI-driven diagnostics platform.
In this high-impact role, you will be responsible for creating scalable, reproducible, and traceable data and ML systems that support the entire lifecycle of clinical AI development—from data ingestion and research to model training, validation, deployment, and monitoring. You will work closely with Software Engineers, Machine Learning Engineers, and clinical stakeholders to ensure the integrity, quality, and regulatory compliance of critical healthcare data.
This position combines Data Engineering, MLOps, and ML Platform Engineering within a highly regulated healthcare environment.

Responsibilities
Design and build robust data ingestion pipelines for large-scale multimodal datasets, including gigapixel pathology images, genomic data, and clinical metadata
Collaborate with Software Engineers to develop testing frameworks, logging systems, and quality controls that ensure complete, accurate, and reliable data processing
Build and maintain scalable data platforms supporting both structured and unstructured data workloads
Develop ML infrastructure that enables reproducible model training, evaluation, deployment, monitoring, and lifecycle management
Ensure data quality, consistency, lineage, and traceability throughout the entire machine learning workflow
Implement compliant frameworks for:
Dataset access management
Model versioning
Experiment tracking
Auditability and governance
Support regulatory requirements aligned with FDA, IVDR, and other healthcare standards
Collaborate with Machine Learning Engineers to improve image processing workflows and data preparation pipelines
Develop containerized, production-grade services for model inference and deployment across on-premises, cloud-based, and OEM-integrated environments
Continuously improve platform reliability, scalability, and operational efficiency

Required Qualifications
4+ years of professional experience in Data Engineering, ML Engineering, Platform Engineering, or related fields
Proven experience building scalable pipelines for large-scale structured and unstructured datasets
Strong experience with Infrastructure-as-Code (IaC) tools such as Terraform, CloudFormation, or similar technologies
Experience designing and operating distributed or high-performance data processing systems
Strong understanding of:
Data modeling
Data warehousing
Data lineage and governance
Distributed computing
MLOps best practices
Experiment tracking and model lifecycle management
Minimum 2 years of experience developing data or machine learning systems in production environments
Experience working in regulated industries such as healthcare, medical devices, life sciences, fintech, or other highly controlled environments
Understanding of reproducibility, auditability, traceability, and compliance requirements in data-driven systems
Strong Python programming skills
Familiarity with at least one deep learning framework such as PyTorch or TensorFlow
Excellent communication skills in English and ability to collaborate across technical and non-technical teams
Valid work authorization within the European Union or Switzerland
Willingness and ability to travel to Tunisia when required

Preferred Qualifications
Experience with healthcare, clinical, pathology, or biomedical data platforms
Exposure to regulatory standards such as:
ISO 27001
ISO 13485
FDA regulations
IVDR requirements
Experience with Software as a Medical Device (SaMD) environments
Knowledge of clinical integrations and healthcare interoperability standards
Experience supporting machine learning systems in production healthcare environments
Familiarity with containerization technologies, Kubernetes, and cloud-native architectures
Experience building secure and compliant ML platforms

⚠️ Important:

Candidates who attach a CV to their application will be prioritized.

• Are you in Berlin and would this be suitable for you (hybrid system; remote work possible after adaptation)?
• Describe your recent experience with similar projects

We are seeking a Python expert to assist with basic visualization tasks. The ideal candidate will have experience in creating simple plots and charts using Python libraries. Responsibilities include developing visualizations to represent data insights and collaborating with our team to ensure the visualizations meet our needs. Familiarity with data visualization tools and techniques is essential.

Machine Learning Engineer

Employment Type: Full-time (40 hours/week)
Duration: Long-term / Permanent
Language Requirements: English (minimum B2 level), German is a plus
Interview Process: 2–3 interview rounds

About the Role
We are seeking an exceptional Machine Learning Engineer to join an innovative AI-driven healthcare company as one of the founding members of the machine learning team. In this highly impactful role, you will lead the development of core AI algorithms that power next-generation diagnostic solutions.
You will work at the intersection of computer vision, deep learning, biomedical image analysis, and product development, helping transform large-scale pathology and imaging data into clinically meaningful insights. This position offers significant ownership, technical freedom, and the opportunity to shape both the company's AI strategy and product roadmap.

Responsibilities
Develop, validate, and document advanced deep learning algorithms for extracting molecular and diagnostic information from whole slide images and other medical imaging data
Lead research and experimentation efforts by defining hypotheses, designing experiments, evaluating results, and iterating on novel approaches
Design and develop innovative computer vision and machine learning models to solve real-world healthcare challenges
Collaborate closely with clinical, product, engineering, and business teams to translate requirements into scalable AI solutions
Work alongside data engineering teams to build robust and compliant data pipelines for processing, traceability, and reproducibility
Contribute to the development and scaling of the company's AI platform, including model integration, deployment, optimization, and monitoring
Develop explainability and interpretability methods to increase transparency, clinical trust, and model validation
Support the generation of clinical validation evidence required for regulatory approvals and market adoption
Continuously improve model performance, reliability, and scalability in production environments

Required Qualifications
PhD in Computer Vision, Biomedical Image Analysis, Machine Learning, Artificial Intelligence, or a related technical field
4+ years of industry experience in Computer Vision or Machine Learning
Strong programming skills in Python
Hands-on experience with at least one major deep learning framework such as PyTorch or TensorFlow
Proven expertise in:
Image segmentation
Object detection
Feature extraction from large-scale and high-resolution image datasets (e.g., whole slide images)
Experience designing and implementing novel deep learning architectures applied to real-world datasets
Minimum 2 years of experience working with:
Cloud infrastructure (AWS, GCP, or Azure)
Data pipelines
Deployment of machine learning models into production environments
Strong understanding of software engineering best practices, version control, and collaborative Git workflows
Passion for clean code, documentation, maintainability, and reproducible research
Excellent communication skills in English and ability to collaborate across multidisciplinary teams
Ability to work independently in a fast-paced, innovative environment
Valid work authorization within the European Union or Switzerland

Preferred Qualifications
Experience in digital pathology, histopathology, or medical imaging
Academic or professional background in biology, pathology, or life sciences
Understanding of cellular morphology and biological image analysis
Familiarity with regulated healthcare environments and medical device development
Experience with regulatory frameworks such as FDA, CE Marking, IVDR, or similar standards
Knowledge of Explainable AI (XAI) techniques and model interpretability methods
Previous experience working with clinical datasets and healthcare AI products


⚠️ Important:

Candidates who attach a CV to their application will be prioritized.

• Are you in Berlin and would this be suitable for you (hybrid system; remote work possible after adaptation)?
• Describe your recent experience with similar projects

Software Engineer (Platform & Clinical Integrations)

Employment Type: Full-time (40 hours/week)
Language Requirements: English (minimum B2 level), German is a plus
Interview Process: 2–3 interview rounds

About the Role
We are looking for an experienced Software Engineer (Platform & Clinical Integrations) to help build and scale the core infrastructure of an innovative AI-powered diagnostics platform. This role combines backend engineering, cloud infrastructure, platform operations, and clinical systems integration.
You will play a key role in designing secure, reliable, and scalable systems that support the deployment of AI solutions within clinical and diagnostic environments. This is a high-impact position with significant ownership and the opportunity to shape how AI technologies are integrated into healthcare workflows.

Responsibilities
Design, build, and maintain scalable cloud infrastructure using Infrastructure-as-Code (IaC)
Develop and operate CI/CD pipelines to enable secure, reliable, and auditable software deployments
Build and maintain backend services and APIs supporting clinical workflows and platform functionality
Develop integrations with Laboratory Information Systems (LIS) and healthcare platforms using standards such as HL7 and FHIR
Create internal tools and lightweight frontend applications for clinical and operational users
Implement and maintain security, monitoring, observability, and compliance controls aligned with standards such as ISO 27001, HIPAA, and GDPR
Ensure high system reliability, traceability, auditability, and operational excellence across all platform components
Collaborate closely with product, engineering, and clinical stakeholders to support platform growth and adoption

Required Qualifications
4+ years of professional experience in Software Engineering, Platform Engineering, DevOps, Infrastructure Engineering, or a related field
Strong hands-on experience with cloud platforms such as AWS or Google Cloud Platform (GCP)
Solid experience with Kubernetes and containerized environments
Proven expertise with Infrastructure-as-Code tools such as Terraform, Pulumi, or similar technologies
Experience building and maintaining production-grade backend systems using Python, Go, Java, or comparable technologies
Experience developing frontend applications with React and TypeScript
Strong understanding of CI/CD pipelines, observability, monitoring, and distributed systems
Experience working in regulated or high-reliability industries such as healthcare, fintech, medical devices, or similar environments
Valid work authorization for the European Union or Switzerland

Preferred Qualifications
Experience integrating Laboratory Information Systems (LIS)
Knowledge of healthcare interoperability standards such as HL7, FHIR, and DICOM
Experience building systems that require strong auditability, traceability, and regulatory compliance
Familiarity with clinical, diagnostic, or laboratory workflows
Previous experience working in healthcare technology, digital health, or AI-driven medical solutions

⚠️ Important:

Candidates who attach a CV to their application will be prioritized.

• Are you in Berlin and would this be suitable for you (hybrid system; remote work possible after adaptation)?
• Describe your recent experience with similar projects

We are looking for an experienced data scraping specialist to extract the complete product catalogue from Reece.com.au.

**Scope of Work:**

* Scrape all product data across all categories.
* Extract product name, SKU/product code, description, specifications, pricing (if available), category hierarchy, brand, images, documents, and any other relevant product attributes.
* Deliver data in a structured format (CSV, Excel, JSON, or database-ready format).
* Identify and handle pagination, dynamic content, and product variants.
* Ensure high data accuracy and completeness.
* Provide a summary of total products extracted and data quality checks performed.

**Requirements:**

* Proven experience with large-scale web scraping projects.
* Strong knowledge of Python, Scrapy, Selenium, Playwright, or similar tools.
* Experience extracting data from complex e-commerce websites.
* Ability to work around anti-bot measures while complying with applicable laws and website terms.
* Excellent attention to detail.

**To Apply:**
Please provide:

1. Examples of similar e-commerce scraping projects you have completed.
2. Your proposed approach for extracting the Reece catalogue.
3. Estimated timeframe and fixed-price quote.
4. Any challenges you foresee and how you would address them.

We are looking for someone who can start immediately and deliver a complete, accurate dataset.

I have 10 (ten) Telegram groups / channels whose member usernames I need extracted in full. Once we begin I will send their exact names so you can join or query them and run the scrape.

Please use any reliable method—custom Python script, Telethon, Pyrogram, or a purpose-built bot—so long as it respects Telegram rate limits and privacy rules. I’m only after the public profile usernames; no phone numbers or private data should be touched.

Deliverables (all mandatory)
• One Excel spreadsheet containing a separate sheet for each group / channel, with columns: Username, Display Name, if available, User ID and Name of Channel it has been sourced from.
• A brief note on the tool or script version used so I can reproduce the results later.
• Confirmation that all data was obtained in accordance with Telegram’s terms and that no group rules were violated.

This is a straightforward scrape, so once you have access the turnaround should be quick. Confidentiality is crucial: do not reuse or share the data. I’ll release payment once I verify the counts match the visible member lists.

Skills: PHP, Python, Data Processing, Web Scraping, Software Architecture, Data Extraction, Data Management, Telegram API

I am currently developing a custom Shift-by-Wire system using an STM32F446RE microcontroller (acting as a Transparent CAN Bridge) to integrate a BMW electronic gear selector into a Range Rover.

The hardware is set up (using SN65HVD230 transceivers), and the basic sniffing/bridging code is functioning. However, because this is a safety-critical system, I am looking for an expert in Automotive CAN Bus Reverse Engineering to assist with the following:

Pre-check Safety Logic: Validating my safety thresholds (e.g., rejecting shifts to D/R if RPM more than 1200 or Speed less than 0 km/h) against standard ZF transmission behavior to prevent TCM faults or mechanical damage.

Bitwise Masking & CRC: Ensuring the 8-byte PRND command injection is done flawlessly without corrupting other critical data within the transmission's CAN message.

State Machine Review: Reviewing the logic where the STM32 handles the "Target Request" from the joystick and waits for the "Actual Status" from the TCM before updating the LED states.

If you have experience with J1939/UDS, TCM spoofing, or Land Rover/BMW CAN architecture, I would love to consult with you to review my architecture and ensure the implementation is 100% safe and reliable.

Looking forward to your feedback.

Cerco sviluppatore Python per realizzare un sistema automatico di monitoraggio delle attestazioni SOA pubblicate sul portale ANAC. L'obiettivo è realizzare un sistema che possa rilevare e notificare nuove attestazioni SOA in tempo reale. Il sistema dovrà essere in grado di gestire grandi quantità di dati e fornire report dettagliati.

**Title:** AI Developer / Full Stack Engineer to Build AI Product End-to-End

**Description:**

We're looking for a strong AI engineer who can take ownership of building an AI product from concept to launch. You'll work across the full stack, design the architecture, and deliver production-ready features with minimal hand-holding.

**What you'll do:**
- Build an AI product end-to-end, from initial scoping to deployment
- Design and implement AI/LLM-powered features (agents, RAG, integrations, automation)
- Develop both frontend and backend components
- Own technical decisions and ship high-quality, well-tested code
- Collaborate closely with us on product direction and iterate quickly

**What we're looking for:**
- Proven experience building AI solutions from scratch
- Strong full stack skills (React/Next.js, Node, Python, or similar)
- Hands-on experience with LLMs, AI agents, APIs, and modern AI tooling
- A keen eye for detail and a high bar for quality
- Clear communicator who collaborates effectively in a remote setting

**Nice to have:**
- Experience with cloud infrastructure (AWS, GCP, or Azure)
- Familiarity with vector databases, prompt engineering, and agentic workflows
- A portfolio of shipped AI products

If you're an experienced AI engineer who loves owning a product end-to-end and sweating the details, we'd love to hear from you. In your proposal, share a relevant project you built from scratch and the AI stack you used.

I currently own a EX4 expert advisor. Since the file is compiled, I am looking to replicate the strategy.

Looking for a MQL4 developer who can spend time understanding the existing strategy via running the file and analysing past historical trade data.

Summary
We are looking for a skilled engineer with strong experience analyzing and integrating with web-based live streaming systems, and who is comfortable using AI development tools such as Claude, ChatGPT, Cursor, or similar tools to speed up development and research workflows.

Your role will focus specifically on understanding how browser-based live streaming platforms function so we can build our own dashboard capable of managing and broadcasting streams programmatically through supported web integrations.

Responsibilities
- Research and analyze live streaming workflows used in modern web platforms
- Analyze browser network traffic, APIs, WebSockets, and real-time communication patterns
- Understand how streams are: Created, Authenticated, Started/stopped, and Maintained in real time
- Develop backend services and automation systems that interact with streaming workflows
- Inspect frontend JavaScript applications and browser runtime behavior to understand platform integrations
- Build proof-of-concept implementations for managing streams from our centralized dashboard
- Work closely with backend engineers to integrate findings into scalable production systems

Analyze:
- WebSocket traffic
- REST/GraphQL APIs
- Binary/protobuf payload structures
- Authentication and session flows
- Real-time heartbeat and telemetry mechanisms

Requirements
- Strong experience working with web-based streaming or real-time communication systems

Deep understanding of:
- WebSockets
- HTTP/HTTPS
- Browser networking
- Real-time communication architectures

Experience with tools such as:
- Chrome DevTools
- mitmproxy
- Burp Suite
- Charles Proxy
- Frida (optional)

- Ability to analyze complex frontend JavaScript applications
- Experience reproducing browser network workflows and session handling
- Familiarity with browser automation, telemetry systems, and anti-abuse protections is a plus
- Comfortable working with undocumented APIs and conducting independent technical research

Strong programming skills in:
- Python
- Node.js
- TypeScript

Nice to Have
- Experience with RTMP, WebRTC, or HLS
- Experience with Puppeteer, Playwright, or Selenium
- Experience working with creator tools or streaming dashboards
- Knowledge of FFmpeg or browser media pipelines

Project Goal
We are building a centralized dashboard that can:
- Control and manage live streams
- Broadcast programmatically through supported web integrations
- Monitor stream status and health
- Automate streaming workflows across platforms

The system should be able to scan repositories, identify APIs/routes, map service dependencies, generate architecture summaries, and create documentation. It should also support multiple programming languages and frameworks, including Python, Node.js, and .NET. The system should be able to generate documentation in various formats, such as Markdown, JSON, and PDF.

Tengo varios ficheros que estoy tratando con power query para transformalos y crear las relaciones en power pivot y hacer un una especie de dashboard. Es un projecto como assesment y me gustraia si podrias ayudarme. LO unico es que me gustaria hacerlo Face to Face en madrid. Dime como lo ves. Un saludo

Wired2Scale — Partnership-Ads Division
Job Specifications
About the division: Wired2Scale runs creator-whitelisting programs for CPG brands. We recruit, vet, brief and scale high-follower creators, run their content as partnership ads, and compound the winners. The goal is to flood our clients' funnels with new visitors and reopen their scaling ceiling. Remote-first, fast-moving, built from zero.



AI/Dev Platform Lead
Reports to: Founder / Head of Partnerships Type / location: Full-time or contract-to-hire · Remote · [confirm] Comp: [band TBC]

Mission Build the creator hub, the masked client portal, and the data pipeline from scratch. Ship fast: no-code where it's faster, real code where it isn't, and AI where it removes manual work. You are the whole technical function at the start.

What you'll own

- The system of record (Airtable or a better fit) and a login-gated, branded client portal (Softr/Glide or custom) with correctly masked client views.
- Daily automated data feeds from Northbeam, Meta & others so spend, revenue, ROAS and tier are never hand-typed.
- Access control and data integrity, especially the masking that hides creator identity and fees from clients.
- Automation for creator sourcing, scoring and vetting.
- AI tooling to speed up brief and script drafting, angle generation, and creator research.
- Reliability and uptime of everything above.

Must-haves

- Has shipped internal tools, portals or dashboards end to end, solo or near-solo.
- Strong with APIs and integrations (REST, webhooks, OAuth).
- Comfortable across no-code (Airtable, Make/Zapier, Softr/Glide) and real code (JavaScript and/or Python).
- Has integrated LLM/AI APIs into working products (OpenAI, Anthropic, or similar), not just experimented.
- Solid data modelling and a bias to ship.

Nice-to-have

- Marketing / ad-data experience (Meta Marketing API, Northbeam, Triple Whale).
- React / Next.js or similar for custom front-end work.
- Dashboard and data-viz experience.

We are looking for an experienced AI/Backend Engineer to troubleshoot and optimize a partially developed RAG (Retrieval-Augmented Generation) pipeline that processes HIPAA-regulated medical documents, including clinical notes, insurance claims, and prior authorization letters.

The application is built using FastAPI, LangChain, OpenAI, and Pinecone, with integration into a Node.js backend. While the system is functional, it is currently producing inaccurate retrieval results and, in rare cases, exposing raw PHI in generated responses. Addressing these issues is critical to ensuring both accuracy and HIPAA compliance.

Scope of Work

- Review and debug the vector embedding and retrieval pipeline.
- Optimize chunk sizing, overlap settings, and metadata filtering to improve retrieval accuracy.
- Update LLM prompts and response handling to ensure PHI is properly redacted before responses are returned.
- Verify that FastAPI endpoints return clean, structured JSON responses, including confidence scores where applicable.
- Confirm that HIPAA audit logging is functioning correctly and capturing all required request activity.
- Test and validate the overall system to ensure reliable, compliant, and accurate output.

Requirements

- Proven experience with RAG systems, LangChain, OpenAI APIs, and Pinecone.
- Strong knowledge of FastAPI and backend API development.
- Familiarity with HIPAA compliance, PHI handling, and healthcare-related applications.
- Ability to quickly identify root causes and implement effective solutions.

The codebase is clean, documented, and ready for review. We are seeking a professional who can efficiently diagnose the issues, implement fixes, and verify that the system meets both accuracy and compliance requirements.

should Build agentic workflows using LangChain/LangGraph and similar frameworks.
• Develop autonomous agents for data validation, reporting, document processing, and domain
workflows.
• Deploy scalable, resilient agent pipelines with monitoring and evaluation.
GenAI Application Engineering
• Develop GenAI applications using models like GPT, Gemini, and LLaMA.
• Implement RAG, vector search, prompt orchestration, and model evaluation.
• Partner with data scientists to productionize POCs.
Data & Platform Engineering
• Build distributed data pipelines (Python, PySpark).
• Develop APIs, SDKs, and integration layers for AI-powered applications.
• Optimize systems for performance and scalability across cloud/hybrid environments.
MLOps / LLMOps
• Contribute to CI/CD workflows for AI models—deployment, testing, monitoring.
• Implement governance, guardrails, and reusable GenAI frameworks.
Collaboration & Stakeholder Engagement
• Work with analytics, product, and engineering teams to define and deliver AI solutions.
• Participate in architecture reviews and iterative development cycles.
• Support knowledge sharing and internal GenAI capability building.

Skills: Java, Python, Mobile App Development, Google App Engine, LangChain, AI Model Development, MLOps, AI Development