Responsibilities
- Design and build end-to-end reinforcement learning systems covering rollout, training, evaluation, and deployment.
- Develop scalable and fault-tolerant RL infrastructure for dynamic workloads and heterogeneous compute environments.
- Optimize distributed training performance across GPU clusters, including throughput, resource utilization, and system stability.
- Collaborate with researchers on system–algorithm co-design and production-grade implementations.
- Build tooling, monitoring, and debugging frameworks for reliability and observability of large-scale RL training systems.
Requirements
- Strong background in distributed systems, large-scale ML systems, or deep learning infrastructure.
- Experience building or optimizing large-scale training systems for RL, LLM, or multimodal models.
- Strong engineering skills in Python and C++, with familiarity with PyTorch and distributed training frameworks.
- Experience with GPU optimization, parallelism strategies, and system-level performance tuning.
- Understanding of RL workflows including rollout, policy updates, and evaluation loops.
- Preferred: experience with large-scale agent systems, heterogeneous or dynamic workload system design, or RL and LLM training or post-training pipelines.
Categories
About ByteDance
ByteDance is a global incubator of platforms at the cutting edge of commerce, content, entertainment and enterprise services - over 2.5bn people interact with ByteDance products including TikTok. Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. We are committed to building a safe, healthy and positive online environment for all our users. We have over 110,000 employees based in more than 30 countries globally. Join us.