Reinforcement Learning Research Engineer

Job Description

Reinforcement Learning Research Engineer

Location - >

Remote (SF / MA Based)

Package - >

$200 – 250k Cash + Benefits

A scaling, SOTA Generative AI Startup operating with a world class team (Founders have multiple prior exits) with talent from Open AI, IBM, MIT and several top orgs, focused on pioneering work and advancements in large language models (LLMs), code generation, and code translation. Their projects directly involve industry leading partners where they’re applying advanced AI to solve meaningful, practical challenges with real-world impact.

Broad Responsibilities :

• Build and maintain robust distributed training systems using PyTorch and JAX
• Build and train production-ready reinforcement learning infrastructure
• Develop orchestration tools that manage complex workflows across large-scale AI model training and evaluation.
• Drive innovation by researching and developing scalable reinforcement learning (RL) algorithms and training paradigms for complex, high-dimensional optimization and decision-making tasks, including recent advancements in RL for feedback-driven optimization in LLMs.
• Design and train large-scale RL environments for optimization problems spanning multiple industries.
• Engage with frontier research through open-source projects and potential publications.

Requirements :

Get in touch today for more details and immediate consideration / interview!