Research scientist - AI Infra - Global Frontier Tech Recruitment Program - 2027 Start (PhD) Glo[...]

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

Benefits offered by this job

Medical insurance

401(k) matching

Paid parental leave

Paid holidays and sick days

Job summary

Pangleglobal is seeking a Research Scientist in AI Infrastructure to join in 2027. Focused on building next-gen AI systems, this role requires a PhD and knowledge in distributed systems and machine learning. Responsibilities include designing scalable AI architectures, tracking AI trends, and optimizing system performance. The position offers a competitive annual salary range of $212,800 - $387,600, along with various benefits including medical insurance and paid time off.

Qualifications

• Completing or recently completed a PhD in Computer Science, Engineering, or related technical field.
• Experience in distributed systems and ML systems.
• Strong proficiency in integrating AI tools into research workflows.
• Excellent communication skills to collaborate across teams.

Responsibilities

• Design and evaluate scalable AI architectures for training and inference workloads.
• Track emerging trends across AI systems and hardware acceleration.
• Analyze and optimize performance across the ML stack.
• Work across teams to translate AI workload requirements into scalable solutions.

Skills

Distributed systems expertise

Infrastructure engineering

Machine learning systems

Excellent communication

Ability to learn quickly

Education

PhD in Computer Science or related field

Tools

Large-scale training pipelines

Data analysis tools

Job description

Research scientist - AI Infra - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

Location: San Jose

Team: Technology

Employment Type: Regular

Job Code: A190405

Responsibilities

We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company. Successful candidates must be able to commit to an onboarding date by the end of year 2027. Please state your availability and graduation date clearly in your resume. Team introduction: 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.

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.

Topic content

1. Network and Observability: Research intelligent fault localization and root cause analysis for large‑scale AI clusters, combined with intelligent tuning of time‑series databases to improve cluster stability.
2. Storage Systems: Develop serverless high‑performance elastic file systems and storage acceleration architectures specifically for AI scenarios, explore hardware‑software co‑optimization for DPU, and overcome AI storage performance bottlenecks.
3. Data Center Power Scheduling: Research GPU/CPU/MEM heterogeneous collaborative scheduling technologies, build a heterogeneous power orchestration system for AI agents, and address scheduling challenges including heterogenous workloads and state dependencies.
4. Vector Retrieval: Optimize core vector retrieval technologies for LLM‑powered applications, building a cloud‑native distributed vector index engine to meet ultra‑large‑scale vector retrieval demands with low latency and low cost.
5. Intelligence and Agent Architecture: Explore automatic infrastructure optimization based on AI Agent workflows, build a self‑evolvable business agent framework, and enable full‑stack intelligent optimization through AI for Infra.

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 $212,800 - $387,600 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.

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

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.

Why Join ByteDance

Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.

As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

Los Angeles County Fair Chance

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.