at Apple
Location
Cupertino, United States of America
Compensation
$181k–$318k USD
Type
full time
Posted
5 days ago
Market range · company + function + seniority
p25 · target · p75 · n=652
Posted $318k · in the market band
Tailor your résumé to this role in 30 seconds.
Free account · ATS keyword check · per-job bullet rewrite by Claude.
We are the team building products for voice, dictation and other audio products at Apple. These are multimodal models that power Siri on-device speech features, and the next generation of audio experiences across our platforms. Our researchers and modeling engineers train models, iterate on data mixtures spanning conductor backed Siri telemetry to synthetic voice corpora, and stack supervised fine-tuning, LoRA adapter training, and reinforcement learning into pipelines that produce the adapters, tokenizers and detokenizers.
You’ll join a small group of production automation engineers whose mandate is to turn the operational substrate underneath foundation model training into a reliable, observable, self-serve system. The work spans python, shell tooling, cloud platform integration, internal CLI design, and close partnership with the product and research teams you are enabling.
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.
Strong software engineering fundamentals; comfortable in Python and Bash, comfortable reading and refactoring large internal codebases.
5+ years experience in Machine Learning Operations.
Production experience with one or more cloud ML platforms (GCP TPU, AWS GPU clusters, Kubernetes-backed training infra) including submitting jobs, debugging schedulers, working around quota systems.
Familiarity with the ML training lifecycle: data preprocessing pipelines, distributed training, checkpoint formats, multi-slice / multi-region considerations.
Experience with infrastructure-as-code, CLI tool design, and developer ergonomics. You've shipped tools that other engineers actually use.
Bias toward observability and reliability.
Comfortable working across team boundaries: you'll partner with researchers, product and infra teams.
Bachelors degree in Computer Science or equivalent technical discipline
Hands-on with JAX, XLA, or large-model training stacks or equivalent.
Experience with multi-slice TPU training and cross-region GCS / S3-compatible storage.
Background in MLOps tools: model registries, feature stores, experiment trackers, reward-model serving for RL.
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.
Join the team redefining what a deeply personal and integrated assistant can be.
As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS.
This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
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Apple accepts applications to this posting on an ongoing basis.
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