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Research Scientist Graduate (Seed-Infra-Machine Learning Sys-US) - 2026 Start (PhD)

Work from home Full-time role Hiring

ByteDance is a leading technology company focused on pioneering advanced AI foundation models. The role involves developing and maintaining large-scale machine learning systems, researching new applications, and collaborating with global teams to enhance intelligent interaction technologies.

Responsibilities

  • Responsible for the machine learning system development of the company's large-scale models, researching new applications and solutions of related technologies in areas such as search, recommendation, advertising, content creation, conversation, and customer service, meeting the growing demand for intelligent interaction from users, and comprehensively improving users' lifestyles and communication methods in the future world
  • Responsible for the design and development of the architecture of large-scale machine learning systems, solving technical difficulties such as high concurrency, high reliability, and high scalability of the system
  • Covering various sub-directions of machine learning system, including resource scheduling, model training, model inference, data management, and workflow orchestration
  • Responsible for the research and introduction of advanced technologies in machine learning systems, such as the latest hardware architecture, heterogeneous computing systems, and compiler-based optimization technologies
  • Working closely with the algorithm teams to optimize the algorithm and system jointly

Skills

  • Final year or recent PhD graduate with a background in Computer Science, related technical field or equivalent industrial research experience
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
  • Excellent coding ability, solid foundation in data structures and basic algorithms, proficient in C/C++ or Python, winners of ACM/ICPC, NOI/IOI and other competitions are preferred
  • Familiar with at least one mainstream machine learning framework (TensorFlow/PyTorch/Jax)
  • Master the principles of distributed systems, and participated in the design, development, and maintenance of large-scale distributed systems
  • Strong sense of responsibility, good learning ability, communication ability, and self-motivation
  • Good communication and collaboration skills, able to explore new technologies with the team and promote technological progress
  • Prior experience in large-scale projects or papers with great influence in the field of large models
  • Familiar with NLP, CV-related algorithms, and technologies, and experienced in large model training and RL algorithms
  • Experience in one of the following fields: CUDA, RDMA, AI Infrastructure, HW/SW Co-Design, High-Performance Computing (cutlass, NCCL), ML Hardware Architecture (GPU, Accelerators, Networking), ML for System, and Distributed Storage
  • Demonstrated a related technical experience from previous internship, work experience, coding competitions, or publications
  • Curiosity towards new technologies and entrepreneurship
  • High levels of creativity and quick problem-solving capabilities

Benefits

  • Medical, dental, and vision insurance
  • 401(k) savings plan with company match
  • Paid parental leave
  • Short-term and long-term disability coverage
  • Life insurance
  • Wellbeing benefits
  • 10 paid holidays per year
  • 10 paid sick days per year
  • 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)

Company Overview

  • ByteDance is a technology company that develops content creation platforms and services. It was founded in 2012, and is headquartered in Beijing, Beijing, CHN, with a workforce of 10001+ employees. Its website is http://bytedance.com.
  • Company H1B Sponsorship

  • ByteDance has a track record of offering H1B sponsorships, with 1350 in 2025, 1123 in 2024, 775 in 2023, 487 in 2022, 417 in 2021, 245 in 2020. Please note that this does not guarantee sponsorship for this specific role.
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