Senior Machine Learning Training GPU Optimization Engineer
3 days ago
Transforming Digital Experiences with Adobe
We're on a mission to empower creators and innovators to design and deliver exceptional digital experiences. As a Senior Machine Learning Training GPU Optimization Engineer at Adobe, you'll play a critical role in shaping the future of digital experiences.
Key Responsibilities:
• Design and implement efficient forward and backward passes in CUDA/CuTe to optimize machine learning training.
• Develop optimized custom layers in PyTorch to accelerate machine learning training.
• Optimize ML training code for large, distributed training with FP8 to improve performance and efficiency.
• Conduct quality and performance analysis between data types such as BF16 and FP8 for large deep learning models.
• Understand and optimize H100 GPUs to maximize their potential.
• Architect broader, end-to-end optimized training code and schemes with PyTorch for large distributed models.
• Write high-quality, product-level code that is easy to maintain and test following standard methodologies.
Requirements:
• Proficiency in at least two of: Linux, Ansible, Docker, Kubernetes (5+ yrs)
• Expert in Python and/or C++
• Expert in CUDA/CuTe, OpenCL, and/or Triton
• Expert in PyTorch
• Experience with DDP, FSDP
• Experience in distributed computing (7+ yrs)
• Experience working with AWS or similar cloud infrastructure (5+ yrs)
• Experience with HW resource management for ML training and/or deployment
• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related area
Compensation:
The pay range for this position is $170,900 -- $325,200 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.
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