Senior Applied ML Engineer — RL & Self-Improving Agents

CoreWeave; Sunnyvale (CA); On-site; USD 182,000 - 242,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with employer match

Equity awards

Flexible PTO

Tuition reimbursement

Job summary

CoreWeave is seeking an experienced AI/ML researcher to push the envelope in self-improving agents and production RL workflows. You will work with the CRAFT team to explore research directions and validate them on real customer tasks, leveraging GPUs and a fast-moving, high-variance environment.

You will contribute to training and deploying ML models, refine techniques for LLM post-training, and collaborate across teams to scale AI.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Robotics, or related field.
• 4+ years of experience in machine learning, or a PhD with 2+ years of relevant industry experience, with a strong focus on model training.
• Strong programming skills in Python and hands on experience with PyTorch or JAX
• Strong understanding of LLM post-training techniques, including supervised fine-tuning, reinforcement learning, and on-policy distillation
• Experience developing, evaluating, and deploying machine learning models in production environments
• Strong research and problem solving skills, with the ability to work effectively in ambiguous, fast moving environments

Skills

Python

PyTorch

JAX

LLM fine-tuning

Reinforcement learning

Production deployment

Education

Bachelor’s/Master’s/PhD in CS/ML/Robotics

Tools

Kubernetes

Megatron

Temporal

Postgres

FastAPI

Job description

CoreWeave is seeking an experienced AI/ML researcher to push the envelope in self-improving agents and production RL workflows. You will work with the CRAFT team to explore research directions and validate them on real customer tasks, leveraging GPUs and a fast-moving, high-variance environment.

You will contribute to training and deploying ML models, refine techniques for LLM post-training, and collaborate across teams to scale AI.