Responsibilitie
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 end of year 2027. Please state your availability and graduation date clearly in your resume. Team Introduction The infra-compute division focuses on building large-scale, highly available Cloud and AI infrastructure. Our work powers both ByteDance's public cloud offerings and its internal corporate products. The US team is dedicated to the research and development of cutting-edge technologies, including training, inference, and AI Agent infrastructure. Responsibilities - Develop key technologies to optimize our AI Infra stack, including training infra, inference infra, and AI agents. - Work with academia and open source communities on joint development. - Follow and research the latest technologies from academia or industry and conduct deep-dive analysis. - Present our research and products in academic papers. Topic Content: With the large-scale adoption of LLMs and AI agents, traditional cloud-native infrastructure can no longer meet the ultra-high performance and elasticity requirements of AI workloads. This topic conducts systematic research across the entire AI infrastructure stack: 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. This topic aims to build a next-generation AI-native infrastructure to support the deployment of LLMs and AI agents, improve resource utilization, reduce costs, support elastic scaling, and drive the technological evolution of AI infrastructure.
Qualification
Minimum Qualifications - Individuals who are completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, Artificial Intelligence or a related technical discipline. - Experience with at least one of the following areas: - LLM training infra, including optimizations for various post-training workloads such as RL training, knowledge distillation, etc. - LLM inference infra, including inference engine performance improvements, more efficient execution parallelism, GPU kernel optimizations, etc. - AI Agents and Agent Infra, including coding agents, general-purpose agents, agent memory, agent sandbox, etc. - Commit to proactive continuous learning, demonstrate enthusiasm for AI technologies, and exhibit a strong ability to quickly grasp and apply new technologies. - Good communication and teamwork skills. Preferred Qualifications - Frequent contributors or maintainers in AI Infra related open source communities such as PyTorch, vLLM or SGLang. - Having publications in CS conferences such as OSDI or MLSys.
Job Information
【For Pay Transparency】Compensation Description (Annually)
The base salary range for this position in the selected city is $207480 - $368220 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.
