AI Acceleration is an org within PyTorch.
It's responsible for making PyTorch run performantly and reliably on new hardware from external vendors (NVIDIA, AMD, etc.
) and Meta's own AI chips.
We are looking for an engineering manager to support internal GPU enablement efforts - using our team's expertise to make GPU inference and training more efficient, reliable, scalable, and simple.
The ideal candidate should have strong technical skills - GPU / ML Systems knowledge is preferred, though not required.
We work closely with internal product groups - XFN is a key part of the job.
We have assembled some of the best engineers in the industry to solve some of the world's most foundational problems at a scale that frankly defies comprehension.
This is a chance to support these engineers and at the same time learn about industry-leading trends in high-performance computation.
Engineering Manager, PyTorch - AI Acceleration Responsibilities:
Grow a team of domain experts within AI Acceleration
Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
Operate strategically and tactically.
Develop vision, strategy and help set direction for the team.
Remain up-to-date on ongoing software development activities in the team, help work through technical challenges, and be involved in design decisions.
Minimum Qualifications:
2+ years of experience in managing a team of HPC/GPU engineers of varied skill levels.
Demonstrated experience recruiting, building, structuring, leading technical organizations, including performance management.
Experience with cross functional collaboration with product ML or AI framework teams.
GPU/CPU optimization skills
Preferred Qualifications:
Knowledge of ML frameworks like PyTorch, TensorFlow, ONNX, MXNet, etc.
Experience with different programming models for high-performance computations, e.
g.
GPU CUDA programming or OpenCL or OpenMP programming.
Experience with ML Systems - GPUs, kernels, compiler, model-specific transformations, quantization, communication optimizations, etc.
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