Role overview
Location**: Remote (EU timezone preferred)
We are looking for an AI/ML engineer to build and scale our AI-powered simulation assistant, which combines LLM orchestration with semantic search in a domain where precision and technical accuracy matter. You will own the full stack from embeddings pipelines to production inference, working closely with physicists and engineers to ground AI outputs in scientific correctness.
What you'll work on
- Design and maintain LLM-based agentic systems for physics simulation workflows
- Build semantic search and retrieval pipelines over technical documentation and simulation data
- Develop embedding pipelines: chunking strategies, vector stores, retrieval evaluation
- Deploy and operate containerized ML services on AWS (ECS, Lambda, S3)
- Optimize LLM inference costs, latency, and quality at scale
- Integrate AI capabilities into IDE extensions (VS Code, Cursor) via MCP
What we're looking for
- Experience with agentic LLM frameworks (LangChain, LlamaIndex, Pydantic AI, DSPy)
- Experience building LLM evaluation pipelines
- Familiarity with MCP (Model Context Protocol) or similar agent-tool interfaces
- Background in scientific/technical domains (physics, engineering, simulation)
- Production AWS experience (EC2, ECS, Lambda)
- Experience with containerization (Docker) and observability tooling
- Knowledge of traditional ML beyond LLMs
Benefits
- Competitive compensation with equity of a fast-growing startup.
- Medical, dental, and vision health insurance.
- 401(k) Contribution.
- Gym allowance.
- Friendly, thoughtful, and intelligent coworkers.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Ai Engineer Machine Learning Generative Ai Ai