Machine Learning Engineer — Reinforcement Learning
Institute of Foundation Models · Sunnyvale, CA
Extracted from the posting
Build and scale end-to-end reinforcement learning training systems for foundation models at MBZUAI's Institute of Foundation Models. The role covers extending distributed training frameworks (DeepSpeed, FSDP, Horovod), integrating rollout engines (vLLM, SGLang) with training workers, and building launch, tracking, and monitoring systems for multi-node, multi-GPU clusters. Stack includes PyTorch or JAX.
About the Institute of Foundation Models
We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.
As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.
The Role
We’re looking for an RL infrastructure engineer to help extend and scale our end-to-end RL training systems. You’ll work side-by-side with world-class researchers and engineers to:
- Extend distributed training frameworks (e.g., DeepSpeed, FSDP, FairScale, Horovod)
- Integrate rollout generation, reward computation, trajectory processing, policy updates, and weight synchronization
- Build robust config + launch systems across multi-node, multi-GPU clusters
- Own experiment tracking, metrics logging, and job monitoring for external visibility
- Improve training system reliability, maintainability, and performance
Hands-on experience developing end-to-end RL infrastructure is required. Strong infrastructure and systems experience is what we value most.
Key Responsibilities
Qualifications
Compensation
$150,000 – $450,000/year + discretionary performance bonus + benefits
The posted salary range represents the company’s good faith estimate of the base compensation for this position upon hire. The actual base compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, and specific business needs. In addition to base salary, total compensation includes an annual discretionary performance bonus and comprehensive benefits.
Benefits Include
- Comprehensive medical, dental, and vision benefits
- Bonus
- 401K Plan
- Generous paid time off, sick leave and holidays
- Paid Parental Leave
- Employee Assistance Program
- Life insurance and disability
Compensation: USD 150,000 – 450,000 per year salary
Job details
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