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

ByteDance; Seattle (WA); On-site; USD 232,560 - 427,500; Full time

Benefits offered by this job

Medical, Dental, and Vision Insurance

401(k) Savings Plan with Company Match

Paid Parental Leave

Paid Holidays and Sick Days

Job summary

ByteDance in Seattle is seeking candidates pursuing a PhD in a relevant field to design and build scalable infrastructure for large-scale model training. The ideal candidate will have excellent coding abilities, especially in C/C++ or Python, and experience in distributed systems or ML.

The role offers a competitive salary range of $232,560 to $427,500 annually and a comprehensive benefits package including medical, dental, vision insurance, and paid time off.

Qualifications

• Currently pursuing a PhD with graduation expected in 2027.
• Excellent coding ability and skills in data structures and algorithms.
• Experience with distributed systems and ML systems.

Responsibilities

• Design and build scalable infrastructure for model training and inference.
• Optimize distributed training systems across compute, memory, and communication.
• Improve system reliability and efficiency for large-scale workloads.

Skills

C/C++

Python

Distributed Systems

Large-scale Training Infrastructure

Education

PhD in Computer Science, Mathematics, Engineering or related field

Job description

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.

Minimum Qualifications

• Currently pursuing a PhD in computer science, mathematics, engineering, or a related field, with an expected graduation date in 2027 and the ability to commit to an onboarding date by the end of 2027.
• Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python.
• Experience in distributed systems, large‑scale training infrastructure, or ML systems.
• Familiarity with deep learning frameworks and system optimization.

Preferred Qualifications

• Strong problem‑solving and engineering skills.
• Strong communication and collaboration skills.

Compensation & Benefits

The base salary range for this position in the selected city is $232,560 - $427,500 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short‑term and long‑term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

Legal & EEO

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues.
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems.
• Exercising sound judgment.