Senior Applied ML Engineer, LLM & RL

CoreWeave; Bellevue (WA); On-site; USD 180,000 - 300,000; Full time

Job summary

CoreWeave is the essential cloud for AI, enabling pioneers to scale AI with confidence. The CRAFT team focuses on building tools to help agents learn from experience, tackling major roadblocks in self-improving agents and expanding the zero-shot and continual learning capabilities across production tasks.

This role demands rapid learning, strong engineering taste, and the ability to ship. You will work with a GPU-rich stack and collaborate with teams to push forward cutting-edge RL and LLM

Qualifications

• 8+ years of experience in machine learning or applied research, or a PhD with 4+ years of relevant industry experience.
• Demonstrated success developing LLM training methods or systems that produce meaningful improvements on real-world tasks
• Deep expertise in LLM post-training, including supervised fine-tuning, reinforcement learning, on-policy distillation, reward modeling, and policy optimization
• Strong research judgment, including the ability to identify high-impact problems, design rigorous experiments, and make decisions from ambiguous results
• Experience taking research ideas from initial hypothesis through implementation, evaluation, and production deployment
• Proven ability to set technical direction, lead complex cross functional initiatives, and mentor other engineers

Responsibilities

• Generate and investigate research ideas towards solving the remaining obstacles to continuous learning in production.
• Validate these research directions across real customer tasks with the broader CRAFT team.
• Work with GPU-rich infrastructure and touch components from CUDA kernels to high-performance LLM tracing dashboards.

Skills

ML research

LLM training

Post-training LLM

Research judgment

End-to-end deployment

Technical leadership

Tools

CUDA

GPU optimization

Job description

CoreWeave is the essential cloud for AI, enabling pioneers to scale AI with confidence. The CRAFT team focuses on building tools to help agents learn from experience, tackling major roadblocks in self-improving agents and expanding the zero-shot and continual learning capabilities across production tasks.

This role demands rapid learning, strong engineering taste, and the ability to ship. You will work with a GPU-rich stack and collaborate with teams to push forward cutting-edge RL and LLM