Senior ML Production Automation Engineer – On-Device AI

Apple; Cupertino (CA); On-site; USD 185,000 - 325,000; Full time

Benefits offered by this job

Stock programs

Bonuses/relocation

Medical and dental coverage

Retirement benefits

Discounted products

Tuition reimbursement

Job summary

Apple is seeking an experienced ML Ops engineer to own end-to-end model pipelines and automation across on-device and distributed training platforms. You will enable rapid iteration, staging, rollout and deprecation while building agent-based workflows and tooling for SFT, LoRA, and RL phases.

Ideal candidates bring strong Python/Bash skills, experience with JAX/XLA, TPU, and cloud ML platforms, and a track record in observability and reliability across complex ML systems.

Qualifications

• Bachelor's degree in Computer Science or equivalent.
• Hands-on with JAX, XLA, or large-model training stacks.
• Experience with multi-slice TPU training and cross-region storage.
• Background in MLOps tools: model registries, feature stores, experiment trackers.
• Prior work simplifying onboarding and access provisioning (Apple Access Manager, AWS IAM at scale, or equivalent).
• Experience writing Claude Code / agent skills, runbooks, or other LLM-assisted developer tooling.

Responsibilities

• Own the end-to-end model lifecycle building model pipelines, integrating with other Apple frameworks to enable rapid model iteration, staging promotion, production rollout and deprecation.
• Design and operate agent-based automation pipelines for ML models where agents own decision logic at each gate and humans approve only at defined escalation points.
• Develop multi-agent workflows using LLM-native tooling for on-device evaluation, regression triage, release readiness decisions, and automated root cause analysis.
• Own the launch tooling to build and improve the shell scripts and CLI commands that turn a config-name and a dataset into a running training job - across SFT, LoRA adapter, and RL phases.

Skills

Python

Bash

ML Ops

Observability

Reliability

Cloud ML platforms

Distributed systems

Education

Bachelor's degree in Computer Science or equivalent

Tools

JAX

XLA

TPU

GCS

S3

Kubernetes

Terraform

Job description

Apple is seeking an experienced ML Ops engineer to own end-to-end model pipelines and automation across on-device and distributed training platforms. You will enable rapid iteration, staging, rollout and deprecation while building agent-based workflows and tooling for SFT, LoRA, and RL phases.

Ideal candidates bring strong Python/Bash skills, experience with JAX/XLA, TPU, and cloud ML platforms, and a track record in observability and reliability across complex ML systems.