Applied AI Research Engineer
Core
Build practical AI research assets including reinforcement learning environments, agentic systems, LLM pipelines, and evaluation harnesses for customer engagements and Frontier lab initiatives.
Role type
Applied AI Research Engineer (Implementation-focused)
Builds
Reinforcement learning environments, agentic systems, LLM pipelines, evaluation benchmarks, and self-hosted model deployments
Domain
Generative AI, Large Language Models, Reinforcement Learning, Model Evaluation
Deliverable
production ML models
Required skills
Software engineering, building agentic systems, reinforcement learning environments, LLM pipelines, evaluation harnesses, model fine-tuning, technical documentation
Preferred skills
Synthetic data generation, published research papers, SWE-bench experience, local inference deployment
Technologies
LLMs, Reinforcement Learning, Self-hosted models
Responsibilities
Build reinforcement learning and agent environments for real customer use cases; Develop benchmarks and evaluation harnesses to measure model quality; Run fine-tuning and adapter experiments; Deploy local or self-hosted models for evaluation and automation; Document experiments and configurations for reproducibility
Seniority
Mid-level, hands-on IC
