Senior Research Scientist/Engineer - AI Infrastructure

ByteDance; San Jose (CA); On-site; USD 212,800 - 387,600; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

401(k) Matching

Paid Parental Leave

Short-Term Disability

Long-Term Disability

Life Insurance

Wellbeing Benefits

Paid Holidays

Paid Sick Days

Paid Personal Time

Job summary

ByteDance is seeking a research‑oriented engineer for the Algorithm team in San Jose. You will design scalable AI factory architectures for training, RL, and inference, and drive cross‑team initiatives across research, hardware, data centers, and product.

You will explore AI memory and system performance, build prototypes, and share insights through technical reports. Strong PhD level fundamentals and collaboration skills are essential.

Qualifications

• PhD in CS/EE or related field with strong systems fundamentals.
• Experience in distributed systems and ML infrastructure.
• Ability to learn quickly and collaborate across teams.

Responsibilities

• AI Factory Architecture – design scalable architectures for AI workloads and trade-offs across hardware and software.
• Research & Technology Exploration – track trends, build prototypes, share insights via reports.
• AI Memory & System Performance Optimization – analyze ML stack and optimize performance.
• Cross‑Team Technical Alignment – translate workload needs into scalable solutions with multiple teams.

Skills

PhD in CS/EE

Distributed systems

ML systems

Communication

Learning agility

Education

PhD in Computer Science/Engineering

Tools

RDMA

NCCL

Job description

Location: San Jose

Team: Algorithm

Employment Type: Regular

Job Code: A59236

Responsibilities

• AI Factory Architecture – Design and evaluate scalable architectures across the full AI factory (compute, storage, networking, chips, power, and the data and application layers) for large‑scale training, RL, and inference workloads. Develop technical proposals for supply‑chain and energy constraints alongside silicon and software trade‑offs.
• Research & Technology Exploration – Track emerging trends across AI systems, distributed training and RL, and hardware acceleration, as well as adjacent fields such as cognitive science and psychology that inform AI memory and reasoning substrates. Build prototypes and share insights through technical reports.
• AI Memory & System Performance Optimization – Analyze and optimize performance across the ML stack (scheduling, networking, storage, training and RL frameworks, and emerging AI memory systems for long‑horizon agents) through benchmarking and bottleneck analysis.
• Cross‑Team Technical Alignment – Work across research, engineering, hardware, data‑center, and product teams to translate AI workload requirements into scalable solutions and drive cross‑team initiatives spanning the full AI factory.

Qualifications

Minimum Qualifications

• Individuals completing or recently completed a PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline. Backgrounds in cognitive science, computational neuroscience, or psychology are also welcome when paired with strong systems fundamentals.
• Experience in distributed systems, infrastructure engineering, or ML systems – including exposure to large‑scale training or RL pipelines – and comfort evaluating trade‑offs across hardware, software, algorithms, energy, and supply‑chain constraints.
• Strong proficiency in integrating AI tools into knowledge discovery and research workflows.
• Demonstrated ability to learn quickly and stay productive on a fast‑evolving technical horizon.
• Excellent communication skills to collaborate across teams.

Preferred Qualifications

• Experience with large‑scale model training and inference – distributed pretraining, post‑training, RL, KV‑cache aware serving, GPU/accelerator optimization, and high‑performance networking (e.g., RDMA, NCCL).
• Experience with heterogeneous AI compute systems, large‑scale training clusters, HPC‑style distributed workloads, and data pipelines for training and evaluation.
• Familiarity with AI memory systems, retrieval‑augmented architectures, or agent long‑term memory designs – bonus for exposure to cognitive‑science or psychology literature on memory and reasoning.
• Exposure to chip‑level design, data‑center energy and cooling, or AI hardware supply‑chain considerations across the AI factory.
• Publications in systems and/or machine learning conferences (e.g., NeurIPS, OSDI, SOSP, ASPLOS, MLSys).
• Contributions to open‑source projects.

Job Information

The base salary range for this position in the selected city is $212800 - $387600 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

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.

For Los Angeles County (unincorporated) Candidates

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:

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

Reasonable Accommodation

ByteDance is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request.