Sr. ML Production Model Automation Engineer, Siri Speech

Apple Inc.; Cupertino (CA); On-site; USD 181,100 - 318,400; Full time

Benefits offered by this job

Comprehensive medical and dental coverage

Retirement benefits

Employee stock purchase plan

Job summary

Apple Inc. in Cupertino, California is looking for an experienced professional to lead the model lifecycle in Machine Learning and AI. This role involves owning model pipelines and integrating them with Apple frameworks to ensure efficient deployments and updates across various platforms.

The ideal candidate will possess strong software engineering skills, experience with cloud ML platforms, and a solid understanding of the ML training lifecycle. This is an opportunity to work at the forefront of AI technology while contributing to innovative product developments.

Qualifications

• 5+ years experience in Machine Learning Operations.
• Production experience with cloud ML platforms including submitting jobs and debugging schedulers.
• Experience with infrastructure-as-code and CLI tool design.

Responsibilities

• Own the end-to-end model lifecycle building model pipelines.
• Design and operate agent-based automation pipelines for ML models.
• Develop multi-agent workflows using LLM-native tooling.

Skills

Software engineering fundamentals

Python

Bash

Machine Learning Operations

Cloud ML platforms

Infrastructure-as-code

Education

Bachelor's degree in Computer Science

Tools

GCP TPU

AWS GPU clusters

Kubernetes

JAX

XLA

Job description

Cupertino, California, United States Machine Learning and AI

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.

Description

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.

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.

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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.

Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.