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On-Device ML Engineering Manager (Tools & Services)

Reads like a Data Leadership role: running a data team.

Seattle

Pay
Pay not listedSimilar roles state $153K–$225K
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Lead the Performance Tools and Services engineering team

  • Oversee frontend and backend web services for introspecting on-device ML execution

  • Oversee the on-device toolchain that collects low-level performance data and maps it to PyTorch ops

  • Oversee infrastructure for running ML inference across fleets of devices

From the employer’s posting
lead the Performance Tools and Services team
responsible for the frontend web services for introspecting ML models and their on-device execution, the backend web services that power them
the on-device toolchain that gathers low-level performance data, associates it with high-level (PyTorch) framework-level ops, and reports it
the infrastructure for running ML inference across fleets of devices

Tools in this posting

  • PyTorch
Source — Tool mentions in context
This infrastructure underpins most of Apple's critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence. Our group is seeking an Engineering Manager to lead the Performance Tools and Services team, with a focus on the tools, services, and infrastructure that make on-device ML performance measurable, understandable, and improvable. The team is responsible for the frontend web services for introspecting ML models and their on-device execution, the backend web services that power them, and the on-device toolchain that gathers low-level performance data, associates it with high-level (PyTorch) framework-level ops, and reports it. The team is also responsible for the infrastructure for running ML inference across fleets of devices.

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Live
First seen by us
Aug 11, 2026 · 80 days ago
Recorded sightings
387
Last seen by us
Oct 31, 2026
Employer says posted
Jul 22, 2026

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Job description

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The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting-edge machine learning models that power magical user experiences on Apple's hardware and software platforms. The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to Apple devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to execute these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations. This infrastructure underpins most of Apple's critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence. Our group is seeking an Engineering Manager to lead the Performance Tools and Services team, with a focus on the tools, services, and infrastructure that make on-device ML performance measurable, understandable, and improvable. The team is responsible for the frontend web services for introspecting ML models and their on-device execution, the backend web services that power them, and the on-device toolchain that gathers low-level performance data, associates it with high-level (PyTorch) framework-level ops, and reports it. The team is also responsible for the infrastructure for running ML inference across fleets of devices.
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Seattle

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