R&D Engineer, Training Infrastructure

About The Team

Our team provide foundational infrastructure and solutions for ML/AI scenarios at ByteDance, including data management for machine learning samples and multimodal data through Magnus, as well as distributed orchestration and computing framework capabilities through Primus and Ray.

Responsibilities

1. Participate in the design and development of Ray-based distributed computing solutions within the company, supporting the Seed large model business.
2. Contribute to feature development and performance optimization for the Ray, KubeRay, and related upper-layer ecosystem frameworks.
3. Build capabilities for running Ray on Kubernetes, including elasticity, tidal resource clusters, stability, observability, and platform integration.
4. Contribute to the Ray open-source community.

Qualifications

Minimum Qualification(s)

1. Bachelor’s degree or above, preferably in Computer Science or a related field.
2. Proficient in programming languages such as Python and C++.
3. Experience with the RayCore/RayData/RayServe or Ray-related frameworks.

Preferred Qualification(s)

1. Familiarity with common distributed computing frameworks, such as Spark/Flink; machine learning background is a plus.