Senior Applied Research Engineer, AI Agents & RL

CoreWeave; Sunnyvale (CA); On-site; USD 207,000 - 275,000; Full time

Benefits offered by this job

Medical, dental & vision insurance (90

ESPP

Paid parental leave

401(k) with company match

Job summary

CoreWeave, The Essential Cloud for AI, is hiring for an applied research role in Sunnyvale, CA. You will generate and validate research ideas to enable continuous learning in production, collaborating with the OpenPipe team to tackle large-scale AI tasks using extensive GPU resources.

You have trained LLMs, evaluated sequence- vs token-level strategies, and driven research from hypothesis to production deployment.

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.

Responsibilities

• Generate and investigate research ideas towards solving remaining obstacles to continuous learning in production.
• Validate research directions across real customer tasks with the broader OpenPipe team.
• Work with GPU-rich infrastructure and push compute at scale.

Skills

8+ years ML/Applied research

PhD + 4+ years

LLM training methods

Education

PhD or related field

Tools

Kubernetes

Megatron

Temporal

Postgres

FastAPI

Job description

CoreWeave, The Essential Cloud for AI, is hiring for an applied research role in Sunnyvale, CA. You will generate and validate research ideas to enable continuous learning in production, collaborating with the OpenPipe team to tackle large-scale AI tasks using extensive GPU resources.

You have trained LLMs, evaluated sequence- vs token-level strategies, and driven research from hypothesis to production deployment.