Research Scientist Graduate (Seed-AI Foundation Model Infrastructure) - 2027 Start (PhD)

ByteDance
Seattle
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: phdSkills: ["Problem-solving","Engineering skills","Communication","Collaboration"]

Work on infrastructure powering AI foundation models, including distributed training, reinforcement learning frameworks, high-performance inference, and heterogeneous hardware compilation. Design and build scalable systems for training, evaluation, and inference; optimize distributed training across compute, memory, and communication; and improve reliability, efficiency, and observability for large-scale workloads. Develop evaluation and data-processing frameworks and co-design systems and algorithms to boost model performance.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
ByteDance
ByteDance
1 month ago

Research Scientist Graduate (Seed-AI Foundation Model Infrastructure) - 2027 Start (PhD)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 30 days agoStatus: Live
Reposted: similar role first listed 1 month ago

Job Summary

Work on infrastructure powering AI foundation models, including distributed training, reinforcement learning frameworks, high-performance inference, and heterogeneous hardware compilation. Design and build scalable systems for training, evaluation, and inference; optimize distributed training across compute, memory, and communication; and improve reliability, efficiency, and observability for large-scale workloads. Develop evaluation and data-processing frameworks and co-design systems and algorithms to boost model performance.
Location: Seattle
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Graduate level

Key Responsibilities

  • •Design and build scalable infrastructure for large-scale model training, evaluation, and inference.
  • •Optimize distributed training systems across compute, memory, and communication.
  • •Improve system reliability, efficiency, and observability for large-scale workloads.
  • •Develop frameworks for evaluation, data processing, and model lifecycle management.
  • •Co-design systems and algorithms to improve performance of foundation models.

Key Requirements

  • •Currently pursuing a PhD in computer science, mathematics, engineering, or a related field, with an expected graduation date in 2027, and able to commit to an onboarding date by the end of 2027.
  • •Excellent coding ability with strong fundamentals in data structures and algorithms, proficient in C/C++ or Python.
  • •Experience with distributed systems, large-scale training infrastructure, or ML systems.
  • •Familiarity with deep learning frameworks and system optimization.
  • •Strong problem-solving and engineering skills, plus communication and collaboration skills.
Experience:Distributed systemsMachine learningDeep learningFoundation models
Education:PhD / Doctorate in computer science, mathematics, engineering, or a related field
Skills:Problem-solvingEngineering skillsCommunicationCollaboration
Tech Stack:CC++Python

Company Brief

ByteDance
Develops consumer internet and content platforms, including TikTok and other apps for short-form video, news, and entertainment. It also builds advertising, commerce, and creator tools that connect audiences, brands, and publishers across global markets.
Industry: Digital Media
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Established Company
Headquarters: Beijing, China
Founded: 2012
WebsiteLinkedIn