Sr. Cloud Ai Infrastructure Engineer

Tencent Music Entertainment Group

Palo Alto, California, US
Base: $145,100.00 to $273,200.00 py; bonus/equity:...
Not specified
Master's or ph.d. in computer engineering
Expertise in gpgpu architectures
Proficiency in cuda and triton
Tencent Music Entertainment Group is seeking a Sr. Cloud AI Infrastructure Engineer in Palo Alto, California, to focus on optimizing AI accelerator architectures and enhancing cloud computing environments. The ideal candidate will have advanced education and expertise in GPGPU architectures, programming frameworks, and distributed systems

Job Summary

  • The role involves conducting in-depth research into the hardware logic of AI accelerators to evaluate power-efficiency ratios for Large Language Model workloads.
  • Candidates will design and optimize high-performance operator libraries while resolving latency issues in memory management and distributed communication.
  • Employees are eligible for a comprehensive benefits package including medical, dental, vision, life insurance, disability coverage, and up to 25 days of vacation.

Matching Summary

Match Score: 85

Tencent Music Entertainment Group is seeking a Sr. Cloud AI Infrastructure Engineer in Palo Alto, California, to focus on optimizing AI accelerator architectures and enhancing cloud computing environments. The ideal candidate will have advanced education and expertise in GPGPU architectures, programming frameworks, and distributed systems.

Salary

Base: $145,100.00 to $273,200.00 per year; Bonus/Equity: Sign-on payment and restricted stock units available; Benefits: Medical, dental, vision, life, disability, 401(k), vacation, holidays, sick leave

Skills & Requirements

Must-have

  • Master's or Ph.D. in Computer Engineering
  • Expertise in GPGPU architectures
  • Proficiency in CUDA and Triton
  • Deep understanding of distributed systems
  • Knowledge of Fat-tree and Torus topologies

Nice-to-have

  • Experience with ultra-large-scale accelerator clusters
  • Low-level adaptation of PyTorch and TensorFlow
  • Feasibility studies on emerging semiconductor trends

Key Requirements

  • Master's or Ph.D. degree required
  • Expertise in GPGPU or AI accelerator architectures
  • Experience with parallel computing frameworks

Work Rights

Not specified

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