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Apple

Manager, Machine Learning Engineering

Posted 28 days ago

Apply on company site View full job

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

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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.

About Apple

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

Size: 10,000+ employees
Industry: Technology: Manufacturing

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