R&D Engineer, Training Infrastructure

About The Team:

Our team provide foundational infrastructure and solutions for ML/AI scenarios at Byte Dance, 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, Kube Ray, 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.

Requirements:

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 Ray Core/Ray Data/Ray Serve or Ray-related frameworks.

Preferred Qualification(s)

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