Research Intern (Frontier AI Systems) - 2027 Start (PhD)

ByteDance; San Jose (CA); On-site; USD 74,000 - 91,000; Full time

Benefits offered by this job

Health insurance

Housing allowance

10 paid holidays per year

Job summary

ByteDance is seeking PhD interns to tackle technically deep problems at the intersection of AI infrastructure, large-scale systems, and memory architectures. You will work with researchers to design and prototype scalable AI factory stacks spanning data, software, chips, and energy components.

Ideal candidates are self-directed, comfortable with ambiguity, and capable of moving between abstraction and implementation.

Qualifications

• PhD candidate in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, or related field.
• Strong background in ML systems, distributed systems, or RL systems.
• Ability to reason across model behavior, runtime performance, and system trade-offs.

Responsibilities

• Conduct research and build prototypes for next-generation AI systems across training, RL, inference, and memory workloads.
• Study bottlenecks, design trade-offs, and improve system efficiency and scalability.
• Develop benchmarking methodologies capturing performance, robustness, and cost in real workloads.
• Collaborate with researchers and engineers to turn ideas into prototype systems and proposals.

Job description

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.

This internship is intended for PhD students who want to work on technically deep, open-ended problems with real systems relevance. We value people who are self-directed, comfortable with ambiguity, able to move between abstraction and implementation, and excited to turn ideas into working systems, measurements, and technical direction.

We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.

Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.

Responsibilities

• Conduct research and build prototypes for next-generation AI systems spanning large-scale training, post-training, reinforcement learning, inference, retrieval, and agentic workloads.
• Study bottlenecks and design trade-offs across the stack, including communication, scheduling, storage, observability, runtime efficiency, memory behavior, and serving infrastructure.
• Develop benchmarking and evaluation methodologies that capture not only raw performance, but also system efficiency, scalability, robustness, and cost under realistic AI workloads.
• Explore new system designs in areas such as distributed training and RL systems, inference optimization, retrieval and memory architectures, agent infrastructure, and heterogeneous hardware-software co-design.
• Work closely with researchers and engineers to turn ideas into prototype systems, empirical insights, and technical proposals that can influence future infrastructure directions.
• Communicate results through clear technical writing, experimental analysis, and collaborative discussion.

Example Research Directions

You may work on one or more of the following areas, depending on background and project fit:

Distributed Training, Post-Training, and RL Systems

Study the systems challenges behind large-scale model development pipelines, including communication bottlenecks, cluster efficiency, scheduling, checkpointing, rollout infrastructure, and resource orchestration for RL and post-training workloads.

Inference and Serving Systems

Design systems for low-latency, high-throughput, and cost-efficient serving of large models, including KV cache management, batching, runtime optimization, memory efficiency, elastic scaling, and accelerator-aware serving architectures.

Retrieval, Memory, and Long-Horizon Agent Infrastructure

Explore infrastructure support for retrieval-augmented systems, AI memory architectures, and long-horizon agents, including vector indexing, memory organization, state management, and coordination across multi-stage agent workflows.

Storage, Networking, and Observability for AI Workloads

Develop system designs for high-performance storage, cluster networking, observability, fault localization, and root cause analysis in large-scale AI environments where training and serving workloads operate under tight performance constraints.

AI for Infrastructure

Investigate how learning-based methods and AI agents can improve infrastructure diagnosis, tuning, orchestration, scheduling, and system optimization for large-scale AI workloads.

Qualifications

Minimum Qualifications

• Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, or a related technical field.
• Strong background in one or more of the following areas: ML systems, distributed systems, large-scale training, inference systems, reinforcement learning systems, storage systems, networking, or infrastructure engineering.
• Strong systems intuition and analytical ability, with the ability to reason across model behavior, runtime performance, and system-level trade-offs.
• Ability to work independently in ambiguous, fast-evolving technical spaces and make progress with limited guidance.
• Strong written and verbal communication skills, and the ability to collaborate effectively with both research and engineering partners.
• Genuine interest in the future of AI systems and infrastructure.

Preferred Qualifications

• Experience with large-scale model training, post-training, or reinforcement learning systems.
• Experience with inference or serving systems, including distributed inference, KV cache optimization, batching, runtime optimization, or accelerator-aware system design.
• Familiarity with retrieval systems, vector indexing, AI memory systems, long-context systems, or infrastructure for agentic workloads.
• Familiarity with large-scale infrastructure concepts such as RDMA, NCCL, cluster scheduling, storage acceleration, heterogeneous compute, or HPC-style workloads.
• Strong research track record, such as publications in machine learning, systems, architecture, or related venues.
• Experience building systems prototypes, research infrastructure, or open-source tools.
• Entrepreneurial mindset and excitement about building in a lean, fast-moving environment.

Job Information

Pay Transparency

Compensation Description (Hourly) - Campus Intern

The hourly rate range for this position in the selected city is $60- $60.

Benefits

• Interns have day one access to health insurance, life insurance, wellbeing benefits and more.
• Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year).
• Interns who are not working 100% remote may also be eligible for housing allowance.

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:

• 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; and
• Exercising sound judgment.

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.

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