Tech Lead, Research Scientist/Engineer - AI Infrastructure

ByteDance; San Jose (CA); On-site; USD 244,800 - 450,000; Full time

Benefits offered by this job

Medical insurance

401(k) match

Parental leave

Wellbeing benefits

Paid holidays

PTO

Job summary

ByteDance in San Jose is seeking an experienced Research Scientist/Engineer to define and build the next generation of AI infrastructure. You will work at the intersection of large-scale systems, AI, and hardware to design scalable, reliable AI workloads across the full stack.

The role involves tracking AI trends, prototyping architectures, and driving innovations in memory systems and performance. Collaboration with leaders and product teams is essential to translate requirements into robust

Qualifications

• PhD in CS, CE, EE or related field; cognitive science background welcomed with strong systems fundamentals.
• Experience with distributed systems, infrastructure engineering, or ML systems and evaluating trade-offs across hardware, software, etc.
• Proficient in integrating AI tools into research workflows.
• Demonstrated ability to learn quickly in fast-evolving tech horizons.
• Excellent cross-team communication skills.

Responsibilities

• Design and evaluate scalable AI factory architectures for large-scale training, RL, and inference workloads.
• Develop technical proposals considering supply-chain and energy constraints alongside silicon/software trade-offs.
• Track emerging AI system trends and build prototypes; share insights via technical reports.
• Analyze and optimize ML stack performance across scheduling, networking, storage, and memory systems.
• Collaborate across research, engineering, hardware, and product teams to translate workloads into scalable solutions.

Skills

PhD in CS/CE/EE

Distributed systems

ML systems

AI tooling integration

Collaborative communication

Education

PhD in CS/EE

Tools

RDMA

NCCL

Job description

Location

San Jose

Team

Algorithm

Employment Type

Regular

Job Code

A108642A

Responsibilities

We are seeking an experienced Research Scientist or Engineer to help define and build the next generation of AI infrastructure. In this role, you will work at the intersection of large-scale systems, AI, and emerging hardware to design infrastructure that enables reliable, efficient, and scalable AI workloads at ByteDance. You will work closely with tech leaders, architects, and product teams to translate evolving AI requirements into robust infrastructure architectures. The role involves identifying emerging trends in AI algorithms and systems, designing scalable system architectures, and driving innovations that improve performance, reliability, and cost efficiency across the AI stack. About the team: We are a lean architect & research team responsible for defining the next generation of AI infrastructure at ByteDance. AI is a fast-evolving horizon — pretraining, RL, and agentic workloads each reshape the requirements faster than traditional cloud abstractions can absorb — and our team is built to keep pace rather than simply react. We approach the problem as an end-to-end AI factory: a tightly coupled production system spanning data, applications, software infrastructure, chips, energy, and the broader supply chain. In this role, you will work at the intersection of large-scale systems, AI, emerging hardware, and the cognitive foundations of intelligent agents — including next‑generation AI memory systems informed by cognitive science and psychology — designing scalable architectures and driving innovations across the full AI factory stack. 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 who are 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 $244800 - $450000 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.

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; and
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