Software Engineer Graduate (AI Compute) - 2027 Start (PhD)

About this role

Software Engineer Graduate (AI Compute) - 2027 Start (PhD)

Location:

San Jose

Team:

Technology

Employment Type:

Regular

Job Code:

A215790A

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Responsibilities

About the Team The Inference Infrastructure team is the creator and open-source maintainer of AIBrix, a Kubernetes-native control plane for large-scale LLM inference. We are part of ByteDance’s Core Compute Infrastructure organization, responsible for designing and operating the platforms that power microservices, big data, distributed storage, machine learning training and inference, and edge computing across multi-cloud and global datacenters. With ByteDance's rapidly growing businesses and a global fleet of machines running hundreds of millions of containers daily, we are building the next generation of cloud-native, GPU-optimized orchestration systems. Our mission is to deliver infrastructure that is highly performant, massively scalable, cost-efficient, and easy to use—enabling both internal and external developers to bring AI workloads from research to production at scale. We are expanding our focus on LLM inference infrastructure to support new AI workloads, and are looking for engineers passionate about cloud-native systems, scheduling, and GPU acceleration. You'll work in a hyper-scale environment, collaborate with world-class engineers, contribute to the open-source community, and help shape the future of AI inference infrastructure globally. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Responsibilities

• Design and build large-scale, container-based cluster management and orchestration systems with extreme performance, scalability, and resilience.
• Architect next-generation cloud-native GPU and AI accelerator infrastructure to deliver cost-efficient and secure ML platforms.
• Collaborate across teams to deliver world-class inference solutions using vLLM, SGLang, TensorRT-LLM, and other LLM engines.
• Stay current with the latest advances in open source (Kubernetes, Ray, etc.), AI/ML and LLM infrastructure, and systems research; integrate best practices into production systems.
• Write high-quality, production-ready code that is maintainable, testable, and scalable.

Qualifications

Minimum Qualifications:

• Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Strong understanding of large model inference, distributed and parallel systems, and/or high-performance networking systems.
• Hands-on experience building cloud or ML infrastructure in areas such as resource management, scheduling, request routing, monitoring, or orchestration.
• Solid knowledge of container and orchestration technologies (Docker, Kubernetes).
• Proficiency in at least one major programming language (Go, Rust, Python, or C++). Preferred Qualifications:
• Experience contributing to or operating large-scale cluster management systems (e.g., Kubernetes, Ray).
• Experience with workload scheduling, GPU orchestration, scaling, and isolation in production environments.
• Hands-on experience with GPU programming (CUDA) or inference engines (vLLM, SGLang, TensorRT-LLM).
• Familiarity with public cloud providers (AWS, Azure, GCP) and their ML platforms (SageMaker, Azure ML, Vertex AI).
• Strong knowledge of ML systems (Ray, DeepSpeed, PyTorch) and distributed training/inference platforms.
• Excellent communication skills and ability to collaborate across global, cross-functional teams. Passion for system efficiency, performance optimization, and open-source innovation.

Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $162000 - $316800 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.​