Senior Machine Learning Engineer

Job Description As a Senior ML Engineer, you build production grade multi agentic systemsthat guide people through complex, high-stakes conversations. Our systems combine multi-step agent orchestration, retrieval, memory, and rigorous evaluation and safety layers.

We're looking for a Senior ML Engineer to design, build, tune, and evaluate these agentic systems end to end — from context engineering and tool design, through retrieval and memory, to evaluation and safety guardrails. This is an applied-ML and LLM-systems role focused on agent behavior, model selection, retrieval of quality, and evaluation.

Though understanding of AI/ML is crucial for this role, we kindly request that you refrain from using GenAI while going through the interview process to allow fair evaluation of your skillset.

What

you’ll do

* Design and orchestrate multi-agentic workflows. * Own context engineering for production agents, including system design, safety rules, context injection, and clarifying question strategies. * Design tools and function-calling interfaces, so agents take reliable, well-structured actions. * Build and tune retrieval (RAG) pipelines — embeddings, vector search, filtering, query rewriting, and relevance tuning. * Select and optimize models across providers, balance quality, latency, determinism, and cost. * Design agent memory and context management for coherent multi-turn behavior. * Build safety and guardrail layers for input filtering, scope and safety checks, and graceful handling of edge cases. * Own LLM evaluation, offline eval suites, graders/LLM-as-judge, test sets and personas, metrics, and quality gates. * Collaborate with cross-functional stakeholders on requirements, project execution and status tracking. * Meta technical responsibility: Document high-fidelity technical designs, establish alignment on solutions within broader engineering team. What we’re looking for

* Bachelor's or...