Member of Technical Staff - Code Generation
About The Position
Introducing Moonlake, AI for creating world simulations. Mission : As an applied AI Research Engineer: Code agents (post training + systems) Scope of Work : - Agentic systems design: Tool catalogs, function calling, program synthesis/repair loops, ReAct/Reflexion/ToT/LangGraph-style control, self-verification, sandboxed execution. - Evaluation mindset: Build task suites for multi-step coding Full-stack LLM engineer: Prompt libraries, routing, retrieval, KV-cache management, streaming, telemetry. - Security & isolation: Docker/firejail, network egress controls, secrets hygiene, dependency pinning, supply-chain sanity. - Strong post-training: Supervised fine-tuning + preference/trace RL (DPO/RLAIF/RLHF), dataset curation, reward shaping, safety filters.
Requirements
- Has shipped agents that pass real repos' test suites end-to-end.
- Has published papers in agentic systems/ code gen
- Contributions to agent frameworks or OSS evals (LangGraph/AutoGen/Guidance/LEAP, SWE-bench variants, EvalPlus).
- Built datasets from execution traces; can show improvements from data > params.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Education Level
No Education Listed
