Senior Applied Research Engineer
Core
Building tools and research to enable self-improving AI agents to learn from experience and perform long tasks autonomously.
Role type
Senior Applied Research Engineer (LLM Post-Training & Agent Learning)
Builds
Serverless RL platform, simulated environments, and training infrastructure for autonomous agents.
Domain
Artificial Intelligence / Machine Learning / Reinforcement Learning
Deliverable
production ML models
Required skills
LLM post-training techniques, reinforcement learning, on-policy distillation, Python programming, PyTorch or JAX, model training, production deployment, CUDA kernels, distributed training, GPU acceleration
Preferred skills
Publications in LLM post-training, open source contributions, leading technically complex projects, mentoring engineers
Technologies
Kubernetes, Megatron, Temporal, Postgres, FastAPI
Responsibilities
Generate and investigate research ideas for continuous learning in production, validate research directions across real customer tasks, develop and deploy machine learning models, work with CUDA kernels and high-performance LLM tracing dashboards
Seniority
Senior, hands-on IC
