New US based .NET team tasked with making an existing, modern platform utilize Microsoft's latest suite of enterprise AI tools and services.This Jobot Job is hosted by: Charles Simmons
Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume.
Salary: $140,000 - $180,000 per year
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 DetailsYou'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
- Extend.ai 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
Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.
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