Staff/Sr. ML Compute Efficiency Engineer

Santa Clara, CA, US • Posted 60+ days ago • Updated 1 hour ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • High Performance Computing
  • IDLE
  • Recovery
  • Scheduling
  • Orchestration
  • Artificial Intelligence
  • Software Engineering
  • PyTorch
  • JAX
  • C
  • C++
  • Python
  • Machine Learning (ML)
  • Research
  • Training
  • Computer Science
  • Articulate

Summary

Scaling machine learning workloads across thousands of GPUs and TPUs creates challenges that few engineers ever encounter. In Apple's Machine Learning Platform Technologies organization, we build the infrastructure that powers large-scale ML training and inference workloads, bringing together expertise in distributed systems, machine learning infrastructure, and high-performance computing.

Description

As a performance engineer in the ML Compute Efficiency team, you'll tackle ambiguous systems challenges, identify inefficiencies and build solutions that maximize accelerator utilization, reduce idle and fragmented capacity, and minimize recovery periods. This includes analyzing accelerator performance, digging into various parallelism techniques, and refining workload scheduling and orchestration across the compute fleet.

Minimum Qualifications

Experience with large-scale distributed systems for AI/ML workloads running on GPUs or TPUs.

Strong software engineering skills with experience developing and optimizing training frameworks (e.g. PyTorch, JAX) using C/C++ or Python.

Experience working on cross-functional projects with ML research and infrastructure teams.

Familiarity with model architectures and various training techniques.

Bachelor's degree in Computer Science or equivalent experience, with 7+ years of industry experience.

Preferred Qualifications

Have a track record of delivering transformative performance improvements on large scale infrastructure.

Ability to analyze ambiguous, distributed systems problems and articulate both high-level strategic metrics and underlying technical complexity.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90733111
  • Position Id: fde904f7dadea28f1f7f59d1b09e8af0
  • Posted 30+ days ago
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