What I Need Help With I have already set up my Raspberry Pi 5 and microscope camera. I am looking for someone to help implement the software pipeline for my project. Specifically, I need assistance with: Setting up and organizing the Python project structure. Use machine learning to be able to identify changes in morphology for each group over time (16 different experimental groups = 16 analysis folders to be compared to each other through ML) Building an automated workflow that processes microscope images using a custom-trained YOLO (Ultralytics) model. Running object detection on microscope images of Microcystis aeruginosa colonies. Extracting quantitative measurements from each detected colony, including colony count, area, equivalent diameter, circularity, and density. Automatically exporting all measurements into a CSV or Excel spreadsheet, with one row of data per image, and each piece of data being tracked based on which group it was taken from. Saving annotated images showing the YOLO detections for later review. Writing clean, modular, and well-documented Python code Troubleshooting any software or integration issues that arise during development.

We’re looking for a developer who knows Python, Rust, and microservices to fix a bug on our AI platform. Right now, some records show up in UTC while others show in local time, and it’s causing inconsistent data across the site. The job is to track down where the mismatch happens, set a single standard for time handling, and make sure everything lines up across the system. Experience fixing production bugs and working with distributed services is a big plus.

Technical Skills: Languages: PHP, Python, JavaScript, SQL Databases & Tools: MySQL, PostgreSQL, MongoDB DevOps & Infrastructure: AWS, Docker, Kubernetes, Terraform, CloudFormation Version Control & CI/CD: Git, GitHub Job Summary: We are seeking an experienced Senior Software Developer to join our team. In this role, you will design and develop robust integrations with CRM platforms, architect and optimize database solutions, and contribute to our cloud infrastructure as code initiatives. You will work with modern technologies including PHP, Python, SQL, and AWS while managing containerized applications, implementing CI/CD pipelines, and interfacing with third party development teams. This is a full-stack role bridging backend development with DevOps practices. Key Responsibilities: - Design, develop, and maintain CRM integrations with leading platforms such as Salesforce, HubSpot, and Actionstep - Architect and optimize database solutions, including schema design, indexing strategies, performance tuning, and backup strategies - Design and implement Infrastructure as Code (IaC) with AWS - Develop, deploy, and manage Docker containerized applications using Docker Compose and container orchestration tools - Write clean, maintainable code in Javascript, PHP and Python - Develop and execute complex SQL queries for data extraction, transformation, reporting, and ETL pipeline development - Configure and optimize AWS services including EC2, RDS, S3, VPC, security groups, and IAM policies - Implement and maintain CI/CD pipelines for automated testing, building, and deployment - Establish monitoring, logging, and alerting systems for production environments - Conduct code reviews and provide constructive feedback to team members - Troubleshoot and resolve production issues with minimal downtime, implementing reliability improvements Required Qualifications: - 7+ years of professional software development experience - Advanced proficiency in PHP, Javascript, & Python - Expert-level SQL knowledge with experience in relational database design, optimization, and data warehouse architecture - Proven experience developing CRM integrations with REST APIs. - Experience with version control systems (Git) and CI/CD pipelines - Hands-on experience with AWS services including EC2, RDS, S3, VPC, security groups, and IAM - Proficiency with Docker and container orchestration (Docker Compose, Kubernetes experience preferred) - Experience with Infrastructure as Code tools such as Terraform or CloudFormation - Knowledge of monitoring, logging, and alerting solutions (e.g., CloudWatch, ELK, Prometheus) - Preferred Qualifications - Experience with Actionstep - Experience designing and maintaining data warehouse solutions - Kubernetes experience for container orchestration at scale - Experience with serverless architectures (AWS Lambda) - Contribution to open-source projects - Bachelor's degree in Computer Science, Software Engineering, or related field

We're hiring a senior AI developer to build and deploy AI solutions for a fintech/credit-union platform. The work spans autonomous banking agents, fraud detection, credit scoring, and bill-pay/invoice automation — at the intersection of LLMs, cloud infrastructure, and financial-domain expertise, with security and compliance built in from the start. This is a long-term, ongoing engagement. What you'll do: AI agents & orchestration - Design, build, and deploy multi-agent systems using Amazon Bedrock Agents, LangChain, and related frameworks - Architect agentic workflows for core banking use cases: credit scoring, fraud detection, bill-pay automation, invoice management - Define agent personas, memory strategies, tool-use patterns, and escalation paths for production banking agents LLM engineering - Fine-tune, prompt-engineer, and evaluate LLMs for financial-domain tasks - Build RAG pipelines over credit-union knowledge bases, policy docs, and member data - Implement guardrails, content filtering, and compliance checks for safe, regulated outputs - Monitor performance, hallucination rates, and latency against SLAs Cloud infrastructure (AWS & Azure) - Architect and manage AI/ML workloads on AWS (Bedrock, SageMaker, Lambda, S3, IAM, VPC) and Azure (OpenAI Service, Azure ML, AKS) - Design secure, cost-optimized environments compliant with NCUA, PCI-DSS, and SOC 2 - Implement infrastructure-as-code with Terraform or AWS CDK DevOps & MLOps - Build and maintain CI/CD pipelines (GitHub Actions, Jenkins, CodePipeline, Azure DevOps) - Containerize services with Docker, orchestrate with Kubernetes (EKS/AKS) - Apply MLOps best practices: model versioning, A/B testing, canary deployments, automated rollback - Stand up observability with logging, tracing, and alerting Python development - Write clean, well-tested Python for AI pipelines, REST APIs, and data workflows - Build FastAPI/Flask microservices exposing agent capabilities to frontend and core banking systems - Integrate with financial data sources, core banking APIs, and third-party fintech services Banking applications - Build credit-scoring models using alternative data and explainable AI (XAI) - Develop real-time fraud detection with behavioral analytics, anomaly detection, and auto-decisioning - Create conversational agents for bill pay, account management, and member self-service - Automate invoice workflows: extraction, classification, approval routing, reconciliation - Partner with compliance/risk to keep AI decisions auditable, fair, and regulatory-compliant What you should have: - 5+ years software engineering; 3+ years in AI/ML or LLM engineering - 2+ years building AI for banking, credit unions, or financial services - Hands-on experience with Amazon Bedrock, LangChain, Python, AWS, and infrastructure-as-code - Working knowledge of NCUA, PCI-DSS, SOC 2, GLBA, and Fair Lending requirements - Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or related field Nice to have: - AWS or Azure AI/ML certifications - Open-source LLM experience (Llama, Mistral, Phi) and self-hosted inference (vLLM, Ollama) - Vector databases (Pinecone, OpenSearch, pgvector) - Graph-based fraud networks and graph ML - AI governance / responsible AI framework experience - Prior work at a credit union, community bank, or fintech lending platform To apply, please share: - Your resume highlighting AI and banking project experience - A brief note on your most impactful AI agent or LLM project in a financial-services context - Links to GitHub, portfolio, or published papers (optional but encouraged)

Job Title: Staff-Level AI Engineer (Consulting + Ongoing Maintenance) We are seeking a staff-level AI Engineer to review our existing product codebase, provide expert guidance, and support ongoing maintenance of our AI systems. Tech Stack: AI/ML, Automation, APIs, MLOps, LLMs, NLP, Python, React, JavaScript Responsibilities: - Review and assess our current AI/ML architecture, codebase, and workflows - Provide clear, actionable recommendations to improve performance, scalability, and reliability - Work closely with our team to refine and enhance AI-driven features - Maintain and monitor production systems, including LLM and NLP components - Troubleshoot issues and ensure smooth day-to-day operation of AI services - Contribute to API integrations and automation pipelines Requirements: - Staff-level experience in AI/ML engineering or applied AI systems - Strong hands-on experience with LLMs, NLP, and production ML systems - Solid background in Python and modern AI/ML frameworks - Experience with MLOps practices (deployment, monitoring, scaling) - Familiarity with API design and integration - Working knowledge of React/JavaScript for product collaboration - Ability to quickly understand and improve existing systems Availability & Communication: - Must be available for quick Slack huddles on weekdays - WARNING: We expect prompt responsiveness for urgent discussions; this role is not a fit for candidates who are not able to join quick huddles when needed - Comfortable with ongoing, real-time collaboration Engagement: - Contract or part-time, with potential for long-term involvement If you enjoy diving into existing systems, improving them, and keeping AI products running smoothly in production, we’d love to connect.

About us We're a growing multi-location dental group in South Florida. We've already designed a fleet of 8 internal automation agents — complete written specs, working code templates, and infrastructure in place. We need a skilled developer to build and deploy them. This is implementation work with clear specs, not open-ended R&D. What you'll build Python automation agents that pull data from our practice management system's REST API (auth pattern already proven in production scripts you'll receive) Claude API integrations (drafting appeal letters, patient texts, weekly analyst reports) with a strict de-identification pattern we'll teach you Firebase (Firestore) reads/writes and light updates to existing web dashboards (deployed via Netlify) Scheduling via Windows Task Scheduler; simple HTML email reports Occasional work with HubSpot API and Google Sheets You're a fit if you have 3+ years Python, comfortable with REST APIs, JSON, and error handling Firebase/Firestore experience Experience integrating LLM APIs (Anthropic/OpenAI) Ability to work from an existing codebase and follow written specs precisely Strong written English and reliable weekly availability (EST business hours overlap) Healthcare/HIPAA experience a plus, not required — but you must be willing to learn and follow our PHI handling rules exactly Requirements (non-negotiable — please do not apply if you cannot meet all of these) Located in the United States with US work authorization. No offshore contractors or agencies. Completed W-9 on file before any work begins Background check required (we order and pay for it) Signed NDA and HIPAA Business Associate Agreement (BAA) required before you are granted any access to systems containing Protected Health Information (PHI). This is a healthcare environment — no exceptions. Video call interview with camera on; government ID verification All access granted via individually credentialed accounts (no shared logins), revocable by us at any time How we'll work Paid test task first: build one small agent (~4–6 hrs) from our spec using our template. Paid at your full rate. Then ~10–20 hrs/week building out the remaining agents, one at a time, each with a written "done when" acceptance test After the initial build-out (est. 60–100 hours total), ongoing part-time maintenance and new features for the right person Weekly check-in call; async otherwise To apply Briefly describe a Python + API automation project you built (what it pulled, what it produced, how it was scheduled) Confirm you're US-based and willing to complete a background check and sign a BAA Your hourly rate and weekly availability Start your proposal with the word "HUDDLE" so we know you read this

We're Bizz Vital Clinic LLC, and we have an internal tool that lets our team upload financial documents (invoices, balance sheets, bank statements, reports) and ask questions about them. It's built on Python + FastAPI with OpenAI, LangChain, and ChromaDB, and it's already running. The problem is the PDF parsing. The text extraction isn't reliable, especially with tables and numbers. Rows get dropped, columns get scrambled, and some figures come out wrong. Since the parsed text feeds into our chunking and embeddings, bad parsing means bad answers, and with financial data, we can't have the numbers off. We don't need a rebuild. The rest of the app works fine. We just need someone to look at the parsing part, figure out what's going wrong, and fix it so extraction (including tables and numbers) is accurate. Stack: Python, FastAPI, OpenAI API, LangChain, ChromaDB, Docker What we need: - Review the current PDF parsing code - Find out why extraction is inaccurate - Fix it (open to switching libraries if needed: pdfplumber, PyMuPDF, Camelot, Unstructured, etc.) - Make sure tables and numbers come through correctly - Confirm the fix improves answer accuracy without breaking the existing pipeline It's a focused bug fix, but the codebase is fairly large, so you'll need to be comfortable working in existing code. When applying, please share: - A similar PDF parsing/data extraction problem you've handled before - A quick note on how you'd approach diagnosing this

Need full stack developer capable of setting up a geospatial software. Software code is written primarily in React and Python. Some coding development will be needed. The ideal candidate will have experience with AWS services and be able to handle both front-end and back-end development tasks. Experience establishing CI/CD pipeline and using GitHub. Experience with Kubernetes cluster (AWS EKS) and Key Cloak identity server. All source code has been developed, need help deploying on new AWS instance. NDA is required. Seeking project completion in 30 days.

Building an AI-powered trading intelligence platform backed by one of the biggest stock-trading YouTubers in the space (7-figure audience, direct distribution to our exact target users from day one). We're not looking for product-market fit — we have a warm audience waiting. We're in the final push to V1 launch and shipping fast. What we've already built An AI Strategy Builder: traders describe a strategy in plain English, our LangGraph agent pipeline (Claude) turns it into code, and a NautilusTrader engine backtests it against years of tick-accurate market data A real data moat: TimescaleDB with 10 years of futures/equities data Live market intelligence: screeners, regime classification, probability models What you'll build You'd own big, meaty features end to end - not tickets, not maintenance: The strategy optimization engine: run 60+ market signals as filters over backtest results, rank by statistical impact, present improvements to users (this is our flagship differentiator) Statistical validation: walk-forward testing, overfitting protection Market calculators: VWAP, volume profile, pre-market levels A daily AI trading playbook delivered via text/Discord Real-time pipeline health monitoring Our stack Python/FastAPI · LangGraph + Claude (Anthropic API) · NautilusTrader · TimescaleDB/Postgres · React/TypeScript/Vite · NestJS · WebSockets · AWS Who we need Someone cracked. Specifically: 5+ years shipping production Python backends (FastAPI/Django/Flask) — you write code that survives contact with real users Real LLM engineering experience — agent pipelines, structured outputs, prompt-driven codegen, LangGraph/LangChain (or you've built equivalents from scratch) Strong SQL and data chops — you're comfortable with time-series data at scale Full-stack ability — you can carry a feature from Postgres to React without waiting on anyone Trading/quant/fintech domain experience is a big plus — you know what Sharpe, drawdown, and walk-forward mean without Googling You ship daily, communicate crisply in Slack, and don't need a PM to translate ambiguity into work Why this gig Direct line to founders, zero bureaucracy — your code hits production the week you write it Guaranteed distribution at launch via our backer's audience — your work gets used by thousands of real traders immediately Long-term engagement for the right person, with room to grow into a lead role

ONSITE WORK REQUIRED We are seeking a network automation consultant with strong Python skills to configure an enterprise-level network for our home office in Alpharetta, GA. The ideal candidate will have experience in network security and administration, ensuring a secure and efficient network setup. This is a small scale project expected to last less than 5 days. However, should there be a good fit between consultant and client, there is strong potential for ongoing Managed Services agreement.