For EmployersCoach ConnectReviewsAbout FairygodbossCareers @ FairygodbossPrivacy PolicyTerms & Conditions
Fairygodboss
CommunityJobsAdviceEventsReviewsFor EmployersCoach Connect
Sign inGet StartedGet started
CommunityJobsAdviceEvents
Apple

Manager, Machine Learning Engineering

27 days ago• China

About us

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

★ 3.7 out of 5 · 120 reviews

  • Size: 10,000+ employees
  • Industry: Technology: Manufacturing
View company profile ›

Why you should apply for a job to Apple:

  • Ranked as one of the Best Technology Companies in 2020
  • 3.7/5 in overall job satisfaction
  • 3.1/5 in supportive management
  • 66% say women are treated fairly and equally to men
  • 65% would recommend this company to other women
  • 66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

The Manufacturing Design team enables the mass creation of impossible products of Apple's entire product line, from iPhone, iPad, and Mac to Apple Watch. A key enabler of this success is a robust set of applications and systems designed to support the product lifecycle from prototype to announcement and beyond.

The applications we build are used daily by the teams managing Apple's supply chain and manufacturing. We collaborate closely with cross-functional partners to architect reliable, 24/7 systems that solve complex challenges in producing the highest quality Apple products.

Description
We are seeking an experienced and motivated Machine Learning Engineering Manager to lead a specialized team of ML and MLOps Engineers. The ideal candidate combines technical expertise in AI with strong leadership skills to drive engineering excellence and deliver high-quality ML systems aligned with business objectives. You will be responsible for executing the technical vision for critical AI-driven manufacturing applications at Apple, leading the team responsible for building, deploying, and scaling them. You possess the strategic foresight to anticipate challenges without over-engineering solutions and can articulate clear, simple approaches to complex algorithmic problems.","responsibilities":"Lead, mentor, and inspire a team of Machine Learning and MLOps Engineers to achieve technical excellence and professional growth.
Collaborate with Project Managers, Data Engineers, and Manufacturing stakeholders to define requirements and prioritize high-impact AI use cases.
Define the long-term vision and engineering roadmap, bridging the gap between data science and production operations.
Foster a culture of collaboration, innovation, inclusivity, and accountability.
Recruit, onboard, and retain top engineering talent with specialized skills in Deep Learning, Computer Vision, and MLOps.
Conduct performance reviews, set objectives, and facilitate career development plans for team members.
Plan and manage ML projects to ensure on-time delivery, focusing on successful deployment and user adoption.
Monitor progress and resolve technical roadblocks to ensure alignment with business goals.
Develop and optimize development workflows, tools, and methodologies to improve team efficiency.
Oversee technical architecture, code quality, and the integration of new technologies.
Stay abreast of industry trends and emerging technologies to drive innovation within the team.

Preferred Qualifications
Experience with MLOps frameworks (e.g., Kubeflow, MLflow) and containerization (Docker, Kubernetes).
Experience scaling ML systems with large datasets (Computer Vision or Time-Series).
Experience deploying models to Edge devices (Industrial PCs, Gateways) or mobile devices (CoreML).
Experience with cloud platforms (e.g., AWS) and DevOps practices.
Proficiency in Python, PyTorch/TensorFlow, SQL, and Linux.
Knowledge of Agile/Scrum software development methodologies.
Exposure to Manufacturing, Industrial IoT, or Smart Manufacturing environments is a plus.

Minimum Qualifications
8+ years of experience in Software Engineering, Data Science, or Machine Learning, including 3+ years in a leadership role.
Proven track record of leading teams to deliver scalable, high-quality Machine Learning models into production environments.
Experience building and managing technical teams with a mix of algorithmic and infrastructure expertise.
Experience leading effective development processes to deliver high-quality production code.
Bachelor's degree or higher in Computer Science, Artificial Intelligence, Statistics, or a related field.

Want more jobs like this?

Get jobs in China delivered to your inbox when you sign up.

Additional Information

  • Posted: 27 days ago
Apply on company site
Apply on company site

Similar Jobs

  • Senior Engineering Manager - Applied Machine Learning - AiDPAppleHyderabad, Telangana
  • Senior Machine Learning Engineering Manager, Responsible AI and Safety - AIML/SWEAppleCupertino, CA
  • AIML - Sr Machine Learning Engineering Manager, EvaluationAppleCupertino, CA
  • Machine Learning Engineering Manager, Credit & UnderwritingAdyenSan Francisco, CA
  • Machine Learning Engineering Manager - TikTok BRIC Live IntegrityTikTok
  • Engineering Manager, Machine Learning - Personalize IntelligenceAdyenChicago, IL

Suggested Searches

  • Apple Jobs
  • All Jobs

Search Additional Jobs

  • Remote-Friendly Manager, Machine Learning Engineering Jobs
Fairygodboss

Fairygodboss

  • Community Guidelines
  • Submissions & Editorial Guidelines
  • Privacy Policy
  • Terms & Conditions
  • The Muse

Advice

  • Community
  • Articles
  • Podcasts
  • Research
  • Pregnancy Week by Week
  • Browse Discussions

Jobs

  • Browse All Jobs
  • Remote Jobs
  • Company Reviews
  • Best Companies for Women

Events

  • Events Calendar
  • Virtual Career Fairs

Employers

  • Partner with Us

© 2026 FGB Muse Group Inc.

© 2026 FGB Muse Group Inc. All rights reserved.

  • About
    • About Us
    • Community Partners
  • Careers
  • FAQs
    • Community Guidelines
    • Submissions & Editorial Guidelines
  • Privacy Policy
  • Terms & Conditions