We are seeking a Machine Learning Engineer with a strong background in Computer Vision and ML fundamentals. The ideal candidate will have experience in healthcare and automotive domains. This role requires someone based in the US, with the ability to work for 6+ months. The candidate should be able to integrate into our team seamlessly and contribute to ongoing projects effectively. [IMPORTANT] In order to verify your language preference. please attach your 1 or 2 mins intro video.

I am building Dewy, an early-stage construction technology platform focused on construction buyout and subcontractor quote intelligence. The first MVP is intentionally narrow: users should be able to upload subcontractor quote/proposal documents and receive structured outputs showing included scope, exclusions, assumptions, qualifications, cost structure, alternates, allowances, and potential risk flags. I have already developed the product concept, construction logic, early workflows, and prototype direction using Codex/AI tools. I am not looking for someone to invent the product from scratch. I need a senior AI product engineer who can review what I have, determine what is usable, define a clean MVP architecture, and help turn the current direction into a working private beta. Initial scope: * Review the current prototype/code/product materials. * Identify what should be reused vs. rebuilt. * Recommend the MVP architecture and tech stack. * Define the AI document-processing workflow. * Design the structure for file upload, extraction, editable results, and export. * Help create a realistic build roadmap, timeline, and budget. * Potentially continue into hands-on MVP development if there is a strong fit. Ideal experience: * Full-stack SaaS / MVP development * AI / LLM application development * OpenAI API or similar model integrations * Document extraction or document intelligence workflows * PDF/DOCX parsing and structured data extraction * React / Next.js * Python * APIs and backend workflows * Supabase/Postgres or similar database experience * Vercel or similar deployment experience * Ability to work with a non-technical founder and translate business goals into a practical build plan This is not a full enterprise platform build yet. The first MVP should stay focused on one core workflow: Subcontractor quote documents in → structured buyout intelligence out. Please respond with: 1. Relevant AI/document extraction projects you have built. 2. How you would approach the MVP architecture. 3. Whether you recommend starting with an audit/roadmap before build. 4. Your hourly rate and availability. 5. Whether you are interested in ongoing build involvement after the initial review.

Upwork Job Description Title: AI Agent Coach — Teach Me to Set Up & Build Agents with Claw (Beginner-Friendly, 1-on-1) Overview I'm a business owner who is comfortable with software but not a developer. I want to learn how to set up and use an open-source AI agent platform ("Claw" / OpenClaw-style agent framework) to build my own AI agents. Most importantly, I'm looking for someone who is genuinely comfortable explaining things in plain, non-technical terms and can help me build a strong, lasting understanding — not just get something working. What I'm Looking For You'll act as my personal coach and guide. The #1 requirement is teaching ability: you can take technical concepts and explain them simply, check that I actually understand, and build my confidence step by step. The goal is for me to truly understand how everything works so I can set up the platform and build agents on my own afterward. Teaching is the priority — not doing it all for me. Scope of Work Walk me through installation and setup from scratch, explaining each prerequisite in plain language Explain core concepts in beginner-friendly terms: what an agent is, tools/actions, prompts, memory, and how the pieces fit together Help me connect API keys and any required accounts safely Build 1–2 simple agents together so I learn by doing Show me how to test, debug, and troubleshoot when something breaks Pause regularly to make sure I understand before moving on Provide a short written "cheat sheet" or recording of our sessions so I can refer back About Me Comfortable with platforms like Google Workspace and basic automation Not a programmer — please explain things without heavy jargon, or define terms as we go I learn best by doing, with clear step-by-step guidance, and I like to fully understand things Ideal Candidate (Most Important) Excellent at explaining technical topics in simple, non-technical language Patient, encouraging, and focused on helping me genuinely understand — not just finishing the task Proven experience setting up and building AI agents (please share examples or a portfolio) Hands-on experience with Perplexity (including Comet / Computer) and Claude workspace is strongly preferred Comfortable with live screen-share sessions and teaching in real time Available for follow-up questions between sessions Format & Logistics Live 1-on-1 sessions via screen share (Zoom/Google Meet) Estimated 3–5 sessions of 60–90 minutes each (open to your recommendation) Sessions recorded for my reference To Apply, Please Include A brief description of your experience teaching beginners and building AI agents

Title: Technical Delivery Lead / Orchestrator — AI & Automation Projects (Ongoing, Part-Time) Description: We're looking for a technically strong delivery lead to orchestrate AI and automation builds — not to do the hands-on coding (a dedicated dev team handles that), but to own the layer above it: scoping client needs, translating them into clear build plans, directing the dev team, and quality-checking what they ship. You'd be our technical point person on projects — comfortable on a call with a client or partner one minute, and reviewing the dev team's architecture the next. We need someone who can tell good work from bad, push back when something's off, and keep projects moving without being micromanaged. This is an ongoing, flexible, part-time role across a steady pipeline of work (marketing automation, agentic AI workflows, web/app builds). You'd start on one project to prove fit, then expand from there. Must-haves: - Strong technical background — you've built real things (read code, architect a solution, judge a dev team's work), with hands-on exposure to AI agents / automation (n8n, LangChain/LangGraph, or similar) - Client-facing polish — represent us professionally to clients and partners - Orchestration experience — you've scoped work and directed developers/teams, not just built it yourself - Based on the US West Coast — reliable overlap with both our team and an offshore dev team To apply, please include: To apply, just a few sentences on each: 1. One project where you scoped a client's need, directed a dev team, and delivered — what was yours vs. the team's 2. A line on your technical depth (something you've architected or built) and a line on client-facing work you've done 3. Your quick take: a client wants an "autonomous marketing system" live in 30 days — what's the first thing you'd want to know, and the most common reason these underdeliver? Keep it short — we're after sharp thinking, not a polished pitch. Individuals only — not agencies.

I am looking to partner with a competent dev team (individual or team) to launch AI implementation solutions for small and medium-sized businesses. As a sales professional, I aim to provide innovative solutions that enhance business operations. The ideal candidate will have experience in AI technologies and a strong understanding of business needs.

I am working on a system using AI to review and respond on Google Drive (Shared Drive) folders of PDF's. Using Gemini as a POC I get responses that sometimes reach outside of my specified folders of content, but sometimes, some PDF files are ignored too. Also, when the response to a prompt come back, the sources are linked. However, the links only bring up the first page of the PDF file wherein the linked source material is, AND NOT THE pdf PAGE of the specific info. I need to have the AI (Gemini, Grok, etc.,) be used to query just.... but all, of the PDF files, within a set of folders in Google Drive (Shared Drive), and to respond with linked content. Said links must open to the PDF PAGE, not just the PDF which houses the specific info. In short, I think I need a viewer, but someone who has experience working with AI and PDF's will likely know the issue I am running into. In the end my system will have a UI attached, so there is a lot of possible side work on this project. First I need to build a better POC. For instance, if I open ONE of the PDF files in Google Drive, I can prompt on that file, and the correct PDF page does come up in the viewer, (While no other files are considered for the queried content.) But when I give Gemini many source PDF's or a folder of PDF's, the links only go to the first page pf the PDF with the information used as the sourcwe.

We’re looking for an experienced engineer or trainer to help deliver hands-on AI coding training for engineering teams. The focus is on moving engineers beyond basic Copilot/autocomplete usage into agentic workflows with tools like Claude Code, Codex, GitHub Copilot, and related tooling. Scope: Run practical workshops for engineers Teach Claude Code, Codex, and Copilot workflows Cover task scoping, prompting, reviewing diffs, and code validation Help create assets like CLAUDE.md, agents.md, slash commands, or workflow templates Advise on best practices, cost awareness, security, and team adoption Ideal candidate: Strong software engineering background Hands-on experience with Claude Code, Codex, or similar tools Experience training engineering teams Clear communicator with practical examples Please apply with relevant examples of AI coding workflows, trainings, or engineering teams you’ve supported.

NobleProg is seeking experienced Claude AI Trainers based in California or Colorado to deliver instructor-led training programs for corporate and government clients. We are looking for professionals with at least 2 years of hands-on experience using Claude by Anthropic who can teach practical applications of Generative AI, prompt engineering, workflow automation, and enterprise AI adoption. This is an ongoing contract opportunity with the potential for multiple training engagements. Compensation $1,200/day for onsite training delivery $1,100/day for remote training delivery Responsibilities Deliver live virtual and onsite Claude AI training sessions Teach both introductory and advanced Claude use cases Facilitate hands-on exercises and demonstrations Answer participant questions and provide practical guidance Customize training content to client requirements Stay current with developments in Claude and Generative AI Required Qualifications Minimum 2 years of hands-on experience working with Claude (Anthropic) Experience applying Claude in business, technical, research, or enterprise environments Previous experience delivering training, workshops, webinars, or professional instruction Strong presentation and communication skills Must be located in California or Colorado Preferred Qualifications Experience with ChatGPT, Gemini, Microsoft Copilot, or other AI platforms Background in AI consulting, digital transformation, or enterprise technology Experience training corporate or government clients Familiarity with prompt engineering and AI workflow design To Apply please include: Your city and state Summary of your Claude experience Training or teaching experience Any AI-related certifications, presentations, or training materials We are actively reviewing candidates and are looking to build long-term relationships with exceptional AI trainers for future engagements. Only candidates based in California or Colorado will be considered.

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)

Seeking an experienced freelancer to scope an AI project focused on generating building floor plans. The ideal candidate will have a strong background in architectural design and AI technologies, with the ability to assess project requirements and provide detailed proposals.