Research Engineer - (Seed Model - Infra - Pretraining Infrastructure)

Responsibilities About the Team The Seed Infrastructures team oversees the distributed training, reinforcement learning framework, high-performance inference, and heterogeneous hardware compilation technologies for AI foundation models. Responsibilities - Conduct research and engineering development on large-scale infrastructure to enable efficient pretraining of foundation models, multimodal LLMs, and video generation models - Design and optimize distributed training strategies for model training, including parallelism schemes, computation and communication optimization, and throughput scaling on large GPU clusters - Analyze performance bottlenecks in exascale training systems and propose principled, data-driven optimization methods - Bridge cutting-edge research and large-scale production deployment by translating research ideas into scalable, real-world infrastructure solution Qualification Minimum Qualifications - Bachelor's degree or above in Computer Science, Software Engineering or a related field, with 2+ years of experience in large-scale model training, distributed training systems, or GPU kernel optimization - Solid understanding of large-scale training of LLMs and multimodal models - Proven experience with parallelism strategies (e.g., data, pipeline, expert parallelism) on large GPU clusters, or GPU kernel performance optimization - Strong grasp of algorithm-system co-design and cross-layer optimization for training efficiency, scalability, and reliability - Strong programming skills and hands-on experience implementing production-grade ML systems or infrastructure Preferred Qualifications - Hands-on experience pretraining LLMs, multimodal, or video generation models at scale, or with mainstream distributed training frameworks (e.g., Megatron-LM, DeepSpeed, PyTorch FSDP, NCCL), or with custom kernel development using CUDA or Triton - Publications at top-tier machine learning or systems conferences (e.g., NeurIPS, ICML, MLSys, OSDI, SOSP), or notable open-source contributions to widely used training framework Job Information 【For Pay Transparency】Compensation Description (Annually) The base salary range for this position in the selected city is $254400 - $480000 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.