We're building an AI health companion for women's health and need an experienced AI Architect for weekly consulting sessions (3-5 hours/week). What You'll Do Meet with our team 1-2x per week to review architecture and provide technical guidance Help optimize our AWS Strands/RAG integration for latency, cost, and scalability Advise on conversation management, context handling, and orchestration decisions Guide us through key technical tradeoffs as we move from prototype to production Our Stack Django backend, Flutter frontend, AWS Strands What We Need 5+ years with AI/ML in production, especially RAG/LLM integration and orchestration Experience with AWS Strands and Bedrock Track record with conversation AI architecture and scaling constraints Bonus: healthcare/HIPAA experience, startup advising, Django/Python knowledge Details 3-5 hours/week, flexible remote schedule Initial 3-month engagement Mix of live calls and async reviews

I need help completing this project today. The project sits between data engineering and AI. I have source data that needs to be cleaned, structured, and prepared so it can support both analytics and RAG-style AI workflows. The goal is to create a reliable pipeline that takes raw data, normalizes it, preserves basic metadata/lineage, and outputs clean datasets that can be used for dashboards, vector indexing, or internal AI tools. The work may include: - Reviewing the current source data and structure - Cleaning and normalizing datasets - Designing or improving an ETL/ELT flow - Preparing AI-ready data for RAG or vector search - Adding basic validation checks - Organizing outputs for analytics use - Documenting the final workflow clearly Ideal freelancer has experience with: - Python and SQL - Data engineering / ETL pipelines - Databricks, Spark, or similar tools - RAG data preparation - Data cleaning, validation, and modeling - Cloud data storage such as S3, Postgres, or similar This is urgent and must be completed today. Please only apply if you are available immediately and can work quickly without a lot of hand-holding. When applying, please include: - Your relevant experience with AI-ready data pipelines or RAG data preparation - The tools you would use - Confirmation that you can complete this today - Your estimated timeline for delivery

Senior Software Engineer (AI-Focused, Contract – US) Position Summary W Energy is seeking a Senior Software Engineer (Contract) to help drive the integration of AI capabilities into our core platform. This role is focused on building AI-powered product features, not just experimenting with models—embedding intelligence directly into workflows across our upstream and midstream solutions. You’ll design and implement AI-driven functionality that improves automation and user experience. This includes leveraging LLMs, machine learning models, and modern AI tooling within a production SaaS environment. This is a hands-on role for someone who can move quickly, make pragmatic decisions, and bring AI concepts into real, scalable product features. Responsibilities • Design and implement AI-powered features within the platform (e.g., automation, recommendations, copilots) • Integrate LLMs and/or ML models into existing services and workflows • Evaluate, select, and optimize AI tools, APIs, and frameworks for production use • Collaborate with Product to translate business problems into AI-driven solutions • Build and maintain scalable backend services to support AI functionality • Profile, test, and optimize performance of AI-integrated systems • Ensure reliability, security, and cost-efficiency of AI components in production • Contribute to architecture decisions around AI integration and system design • Partner with engineering teams to embed AI into existing applications without degrading stability Requirements • 5+ years of experience as a software engineer in a SaaS or cloud-based environment • Strong backend engineering experience (RoR and/or Golang preferred) • Experience integrating APIs and working within distributed systems • Hands-on experience with AI/ML tools (e.g., OpenAI, Anthropic, Hugging Face, or similar) • Experience building or integrating AI-powered features into applications (not just experimentation) • Strong understanding of data flow, system design, and performance optimization • Experience with relational databases (SQL Server or similar) • Familiarity with microservices architecture, Kubernetes, and CI/CD pipelines • Experience deploying applications in Azure or similar cloud environments • Strong problem-solving skills with ability to work in ambiguous, fast-moving environments • Builder mindset—someone who can take an idea and turn it into a working feature quickly • Pragmatic approach to AI (focus on value, not hype) • Ability to work independently in a contract environment while collaborating closely with internal teams • Strong communication skills and ability to explain AI concepts to non-technical stakeholders Preferred • Experience with prompt engineering, embeddings, or retrieval-augmented generation (RAG) • Exposure to model evaluation, fine-tuning, or AI performance monitoring • Experience with event-driven architectures or real-time data processing • Background in energy, fintech, or other complex data-driven industries

We are seeking an expert Data Scientist in the United States with 5+ years of experience in linear programming. The ideal candidate will have a strong background in data analysis and machine learning, with the ability to optimize complex systems using linear programming techniques. Responsibilities include developing and implementing data-driven solutions, collaborating with cross-functional teams, and providing insights to drive business decisions. TeamBuilder is a rapidly growing healthcare SaaS company on a mission to transform healthcare with our innovative technology. We believe in empowering our customers through inventive solutions and a commitment to excellence. Our young, rapidly growing team is looking for passionate professionals who thrive in a dynamic, innovative, and collaborative environment. ***This role is FULLY REMOTE, though you MUST reside within the United States and be legally authorized to work in the United States. The Role TeamBuilder builds software for ambulatory healthcare operations. The problem is simple: turn messy healthcare data into actions. This role sits between data, forecasting models, and optimization. You own forecasts end to end and work directly with the optimization layer. Shape inputs, validate outputs, and turn results into something operators can use. What You’ll Do  Forecasting model ownership o Build and iterate production grade demand and volume forecasts o Evaluate models with backtesting and real-world performance o Maintain stability with retraining, drift monitoring, and failure handling o Improve models based on operational outcomes  Sit at intersection of data and optimization o Define input data contracts for optimization models including capacity, constraints, and demand o Transform raw data into model-ready features and constraints o Validate solver outputs and identify infeasibility, constraint conflicts, and scaling issues o Trace issues back to data assumptions and constraint design o Convert outputs into usable schedules and recommendations  Model + system validation o Compare model output to operational reality and explain gaps o Run scenario analyses under different constraints o Improve pipelines that support forecasting and optimization quality o Test assumptions against real-world variation  Communication / translation o Explain models and outputs to non-technical users including operators and clients o Translate tradeoffs between accuracy, feasibility, and constraints o Deliver clear recommendations tied to business outcomes o Participate in client conversations and defend model behavior What We’re Looking For Qualifications  5+ years in data science or applied analytics  Experience owning forecasting models in production  Strong Python and SQL, comfortable with large datasets  Experience working with messy data  Ability to explain technical work clearly to non-technical users Preferred Skills  Experience in healthcare or complex operational environments such as staffing or capacity planning  Experience with capacity-constrained systems  Familiarity with solvers such as Gurobi Why You’ll Love Working Here  Mission-driven team tackling real healthcare challenges.  Freedom to experiment and innovate without layers of bureaucracy.  Opportunity to shape the company’s data science culture and R&D direction.  Flexible work environment and supportive, intellectually curious teammates. Additional Information  Job Type: Contracted, Part-Time/Full-Time, Remote  Compensation: Hourly, project-based. Potential to go Full-Time.  Culture: We foster a collaborative, engaging, mission-driven culture that values innovation and prioritizes customer success.

We are hiring an AI Engineer with strong hands-on experience building and shipping real AI products. Requirement: If you don't have a GitHub profile to share, this role is not a fit. What we’re looking for: • Strong experience in AI/ML engineering • Ability to build, test, and deploy production-ready AI systems • Practical experience working on real-world AI projects To apply: Please share your portfolio, past AI projects, and relevant work samples. Applicants without portfolio will be ignored.

Overview We're building an open-source CLI gateway for multi-agent AI orchestration — model-agnostic, MCP-native, and designed to bring any agent framework online with a single command. The repo is active, well-documented, and growing. We need an engineer to accelerate integration coverage and help attract open-source contributors. The Work Build agent templates and runnable examples for LangGraph, CrewAI, and similar frameworks Add LLM provider support (Groq, Mistral, Gemini, etc.) to the Hermes runtime Write clean, contributor-friendly code that models good PR hygiene Submit work via fork → PR → merge workflow on GitHub You Are Strong Python developer with CLI tooling experience Familiar with at least one of: LangGraph, CrewAI, LiteLLM, LangChain Comfortable with open source GitHub workflows (fork, PR, issues, reviews) Self-directed — you read docs, ask good questions, and don't wait to be unblocked Nice to Have Experience with MCP (Model Context Protocol) Familiarity with SSE, OAuth 2.1, or agent credential management Prior open source contributions Engagement Part-time to start, 20 hrs/week Fixed milestones per integration delivered Potential to grow with the project To Apply Share your GitHub profile and one example of open source work or a project that shows your Python and agent framework experience. https://github.com/ax-platform/ax-gateway

Senior AI/ML Engineer / Claude architect — Legal Tech FirmProfit AI is the operational backbone of the modern law firm. We automate law firm operations end to end, and we're looking for a top-tier AI/ML engineer to help us build the next major platform in legal tech. We need a true expert. Someone deeply proficient with Claude and modern LLM architecture who has shipped real products at a high level. You're fluent across the full stack with Node.js, React, Postgres, MongoDB etc... and you have hands-on experience building with LangChain, LangGraph, MCP, and AWS Bedrock. We're not looking for someone who's read about LLMs. We're looking for someone who has shipped agents, orchestration layers, and production AI systems that real users depend on every day. Our current team is 8 engineers, we have firms signed and live, and we're moving fast. This is a chance to come in early, and have your work in the hands of customers within weeks. Contract to start, with a long-term path for the right person. Reply with the most impressive AI product you've shipped.

Type: Hourly, ongoing (part-time to full-time, room to grow) Stack you'll work in: Notion, Slack, HubSpot, Google Workspace/Gmail, Claude + other LLM APIs, Zapier/Make/n8n About us We're a fast-moving sports and fan-engagement startup. We're small, we ship quickly, and we want AI woven into how the whole company operates, not as a side experiment, but as the default way we work. You'd be the person who makes that real. What you'll do Map our current workflows across sales, marketing, ops, and content, then find the highest-leverage places to automate. Build automations and agent workflows that connect our tools (Notion, Slack, HubSpot, Gmail/Google Workspace) using platforms like Zapier, Make, or n8n plus LLM APIs. Design and ship AI agents for real jobs: lead routing and CRM enrichment, content drafting, customer/fan response triage, internal knowledge search, reporting digests. Stand up the connective tissue (prompts, integrations, guardrails, and monitoring) so automations are reliable, not brittle demos. Train and enable our team: build SOPs, run working sessions, and create lightweight docs so non-technical people actually adopt what you build. Help set our AI strategy and roadmap as we scale. You're a strong fit if you Have shipped real automations and AI agent workflows in production (not just prototypes). Are fluent with Zapier / Make / n8n and at least one major LLM API (Anthropic/Claude, OpenAI). Know your way around HubSpot, Notion, Slack, and Google Workspace integrations and APIs. Can write clean prompts and think in systems: edge cases, error handling, human-in-the-loop checkpoints. Can explain technical work to non-technical people and get them to adopt it. Communicate proactively and move fast without breaking trust on things that touch customers or revenue. Nice to have Experience taking a small company "AI-native" end to end. Background in sports and/or blockchain. Comfort with light scripting (Python/JS) when no-code hits its limits. How to apply In your proposal, please: Describe one AI agent or automation you built, the tools involved, and the measurable result. Tell us how you'd approach training a non-technical team to actually use what you build. This part matters as much as the build. Share your hourly rate and weekly availability. Proposals that skip these will be passed over. We're looking to start with a small paid task and grow the engagement from there.

We are building a semiconductor manufacturing intelligence platform designed to help engineers investigate yield excursions, identify root causes, and capture organizational knowledge. The current platform includes yield monitoring dashboards, process-route visualization, lot tracking, maintenance-event correlation, and investigation timelines. We are now looking for an experienced developer to help evolve the platform into a comprehensive engineering decision-support system. This is not a simple dashboard project. The goal is to create a system that combines manufacturing data, equipment history, engineering knowledge, and AI-driven analysis to accelerate root-cause investigations and improve yield performance. What We Want to Build The platform should help engineers answer questions such as: - Why did yield drop? - What tool or chamber is most likely responsible? - What changed before the excursion began? - Have we seen a similar excursion before? - What corrective actions worked previously? Scope of Work Potential features include: Lot Genealogy & Traceability - Lot and wafer genealogy tracking - Process flow visualization - Traceability across manufacturing steps - Dependency analysis between lots and process routes Equipment & Maintenance Intelligence - Tool and chamber history tracking - Maintenance event correlation - Preventive and corrective maintenance analysis - Equipment performance insights Investigation Workspace - Interactive investigation timelines - Correlation of process events, maintenance activities, SPC/FDC signals, and yield impacts - Root-cause exploration tools Historical Excursion Search - Identification of similar historical excursions - Pattern matching and similarity scoring - Retrieval of previous investigations and outcomes Engineering Knowledge System - Searchable repository for engineering notes - Troubleshooting reports - Process change documentation - Historical corrective actions - Manufacturing best practices AI-Powered Analysis - Automated root-cause summaries - Investigation reports - Suggested contributing factors - Recommendations based on historical data and prior resolutions Ideal Candidate We are looking for someone with experience in one or more of the following: - Manufacturing analytics - Semiconductor data systems - Industrial software platforms - AI/LLM applications - Data engineering - Knowledge management systems - Predictive analytics Experience with semiconductor manufacturing data is a major plus. Proposal Requirements Please include: - Examples of similar projects - Recommended technology stack - Architecture approach - Which features you would prioritize first - Your thoughts on scalability and future expansion We are looking for a long-term technical partner who can help transform the platform from a monitoring dashboard into a manufacturing intelligence system.

Project Overview We are looking for an experienced AI workflow, process design, and prompt engineering expert to help us automate part of our sales and proposal development process. Currently, our project management team spends 4–12 hours developing a custom research plan and proposal for each active FSI lead. In busy weeks, we may work on 5–6 leads, which creates a significant time burden and slows down response time. We want to build a custom ChatGPT skill or AI workflow that can take sales notes, email context, and call notes, then help generate a research plan and proposal in our existing format. What We Need We need someone who can: Learn and map our current sales/proposal process Translate that process into a structured AI workflow Write effective prompts and decision trees Train or configure a custom ChatGPT skill/workflow Help the AI ask the right follow-up questions Generate proposal sections based on uploaded notes Recommend research scope, segmentation, targets, and options Output the final proposal in our existing template Desired Workflow The ideal AI workflow would allow us to upload notes from emails and sales calls. The AI would then ask a series of structured questions to determine how to write each section of the proposal. The AI should be able to: Recommend the appropriate research process Suggest project scope Identify demand segmentation opportunities Create tables for the proposal Recommend constituencies and companies to target Suggest research options Draft the proposal using our template Provide a strong first draft that our team can review and adjust Business Goal The goal is to significantly reduce the time spent developing research plans and proposals, especially for early-stage leads and marketing-generated opportunities. This is particularly important for new leads from companies we have not worked with before, where the probability of closing may be relatively low. We want to respond quickly and professionally without taking excessive time away from active client projects. Ideal Freelancer You should have experience with some or all of the following: AI workflow design Prompt engineering Custom GPTs or ChatGPT skills Sales/proposal automation Business process documentation B2B research or consulting workflows Template-based document generation AI-assisted decision trees Knowledge management or internal AI tools Experience with market research, consulting, or proposal development is a plus. Deliverables We expect the freelancer to deliver: A documented AI workflow/process map A set of structured prompts and instructions A functioning custom GPT, ChatGPT skill, or equivalent AI workflow Question logic for gathering missing proposal inputs Proposal section drafting logic Testing and refinement using sample lead notes Documentation so our team can maintain and improve the workflow Project Type This will likely begin as a one-time project, with potential for ongoing support as we refine the workflow and expand it to other proposal types. To Apply Please include: Examples of AI workflows, custom GPTs, or prompt systems you have built Your experience with proposal automation or business process automation Your recommended approach for this project Any questions you would need answered before starting