Member of Technical Staff - Code Generation

Introducing Moonlake, AI for creating real-time interactive content

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/Lang Graph-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.

Tech signals:

- 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 (Lang Graph/Auto Gen/Guidance/LEAP, SWE-bench variants, Eval Plus).

- Built datasets from execution traces; can show improvements from data > params.

We are committed to being an on-site, in-person team currently based in San Mateo