About this opportunity
Adobe lists this Senior ML Training GPU Optimization Engineer opportunity in san francisco, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
What you will be working on:
Write efficient forward and backward passes in CUDA/CuTe.
Write Optimized custom layers in Pytorch.
Optimize ML training code for large, distributed training with FP8.
Quality and performance analysis between data types such as BF16 and FP8 for large deep learning models.
Understand and optimize H100 GPUs.
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.
What do you need to succeed:
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
B.S., M.S, or Ph.D. in Computer Science, Computer Engineering or a related area
FireflyGenAI
Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this positionis $170,900 -- $325,200 annually. Paywithin this range varies by work locationand 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.
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.