A bit about us: We’re transforming how government agencies digitize forms and automate workflows. Our new initiative brings AI directly into this process - using LLMs, vector search, and structured PDF parsing to accelerate public service delivery. We’re not just bolting AI onto the side. It’s becoming core to how our platform works.

We’re looking for a senior machine learning engineer to take the lead on this effort. You’ll be the architect of our AI capability - not just a contributor. Your work will touch thousands of public-facing government forms, helping real people get things done faster and more accurately. This isn’t an R&D team running experiments - it’s about delivering intelligent automation, right now. Why join us? 100% remote based in the US Help shape the AI transformation of public sector services Lead initiatives that ship real impact, not just prototypes Greenfield development on a proven, profitable platform Comprehensive Health, Vision, Dental coverage for individuals and families Job Details You’ll design and build our machine learning infrastructure - starting with vector search and retrieval-augmented generation and expanding into fine-tuned LLMs with human feedback loops. You’ll work across product and engineering to embed intelligent behaviors into our no-code form builder. This is not a research job or a sandbox role - it’s a real opportunity to push AI into production at scale.

What you’ll do Build and tune vector-based retrieval pipelines using OpenAI embeddings and Azure AI Search Design prompt strategies and agents to translate parsed PDF data into form component schemas Fine-tune LLMs for structured output generation with low-latency performance in mind Lead the development of an RLHF loop that incorporates builder UI feedback and audit data Help architect systems that blend traditional APIs and probabilistic inference reliably Work alongside full-stack and platform engineers to get it all running in production Stay plugged into the latest model capabilities, and make smart calls on what to adopt

Tech you’ll use Azure AI Studio, Azure OpenAI, GPT-4o Python (for agents, functions, orchestration), .NET 8 (for integration layers) Azure AI Search, CosmosDB, MSSQL Kubernetes (AKS), Azure Blob, Octopus for CI/CD for structured PDF parsing

What we’re looking for 5+ years in applied ML, including experience with retrieval, embeddings, and prompt engineering Strong Python skills and familiarity with production-grade ML pipelines Experience designing and tuning RAG workflows with hybrid search Familiarity with RLHF and fine-tuning on structured JSON output Solid grasp of system-level thinking—how to bring ML into product environments cleanly

Nice to have: .NET understanding, especially for integration and orchestration layers

What success looks like in 6 months You’ve shipped a working vector search + RAG pipeline integrated into our form builder You’ve scoped and kicked off our first LLM fine-tuning cycle We’re collecting human feedback to improve model accuracy You’ve helped define the roadmap for AI integrations across the platform Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance.