Research and implement reinforcement learning techniques including GRPO, RLHF, RLAIF, DPO, and reward modeling
Design and build data pipelines that generate high-quality training signal for RL workflows
Prototype and iterate on end-to-end RL training recipes
Work closely with research scientists, ML engineers, and delivery teams
Stay current with the latest developments in large-scale muli-node LLM training

Requirements

Deep expertise in reinforcement learning from human or AI feedback
Experience training or fine-tuning 30B+ large language models at scale
Strong proficiency in Python and ML frameworks, especially PyTorch and HuggingFace
Solid software engineering fundamentals
Familiarity with ML infrastructure and cloud platforms
Comfort operating in a high-iteration environment
Ph.D. in machine learning, reinforcement learning, or a related field strongly preferred

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

reinforcement learningGRPORLHFRLAIFDPOreward modelingPythonPyTorchHuggingFacelarge language models

Soft Skills

collaborationiterationproblem-solving

Certifications

Ph.D. in machine learningPh.D. in reinforcement learning