Manager, Machine Learning Engineering

Apple; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

An established industry player is on the lookout for a visionary Engineering Manager to lead their Machine Learning Rapid Prototyping team. This role is pivotal in driving innovation at the intersection of AI and customer experience, focusing on developing and validating cutting-edge machine learning solutions. You will oversee a dynamic team, champion responsible AI practices, and collaborate with various stakeholders to transform complex challenges into feasible solutions. Join this forward-thinking company in shaping the future of customer support through advanced ML technologies and impactful initiatives.

Qualifications

• 10+ years of experience leading ML/AI initiatives in fast-paced environments.
• Expertise in machine learning, particularly generative AI and knowledge graphs.

Responsibilities

• Lead a cross-functional team in developing innovative ML solutions for customer support.
• Drive strategic direction for ML rapid prototyping initiatives and evaluate emerging technologies.

Skills

Machine Learning

Generative AI

Project Management

Analytical Skills

Problem-Solving

Communication Skills

Education

Bachelor's in Computer Science

Master's or Ph.D. in Computer Science

Tools

PyTorch

TensorFlow

Hugging Face

Job description

Manager, Machine Learning Engineering

Austin, Texas, United States Support and Service

Summary

Posted: Mar 11, 2025

Weekly Hours: 40

Role Number: 200591495

At Apple, groundbreaking ideas transform into revolutionary products, services, and customer experiences. The AppleCare Technologies Engineering team is pioneering the future of customer support through advanced machine learning solutions. We're seeking a visionary Engineering Manager to lead our Machine Learning Rapid Prototyping team, where you'll drive innovation at the intersection of AI and customer experience. Join us in shaping the future of AppleCare through pioneering ML technologies and transformative solutions.

Description

Lead a dynamic cross-functional team in developing and validating innovative machine learning solutions for AppleCare. You will oversee rapid prototyping initiatives, evaluate emerging ML technologies, and transform complex business challenges into feasible solutions while maintaining Apple's high standards for quality and innovation. Key responsibilities:

1. Develop and drive strategic direction for ML rapid prototyping initiatives, evaluating emerging technologies including generative AI and knowledge graphs.
2. Lead and inspire a cross-functional team of ML engineers, data scientists, data engineers, QA specialists, and engineering project managers.
3. Partner with business collaborators to identify, prioritize, and validate ML opportunities.
4. Champion ML standard methodologies including responsible AI development, model governance, and quality assurance.
5. Oversee the full lifecycle of ML proof-of-concepts, from ideation through validation and handoff.
6. Collaborate with engineering teams to ensure successful transition of validated solutions into production.
7. Communicate ML initiatives, outcomes, and insights to senior leadership.
8. Engage as a key member of the AppleCare Technologies Engineering Leadership team.

Minimum Qualifications

1. BSc in Computer Science, Machine Learning, or related field.
2. 10+ years proven experience leading ML/AI initiatives and teams in a fast-paced environment.
3. 5+ years managing global teams.
4. Technical expertise in machine learning, particularly in generative AI, traditional ML, and knowledge graphs.
5. Experience managing rapid prototyping and proof-of-concept development in ML/AI (particularly GenAI).
6. Proficiency in modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face).
7. Experience leading cross-functional technical teams.

Preferred Qualifications

1. Master's degree or Ph.D. in Computer Science, Machine Learning, or related field.
2. Strong understanding of ML operations, including model development, evaluation, and deployment.
3. Outstanding project and program management capabilities.
4. Track record of building strong partnerships with business collaborators.
5. Exceptional communication skills with ability to translate complex ML concepts for various audiences.
6. Results-driven with excellent analytical and problem-solving abilities.
7. Experience with large-scale ML deployments in customer service environments.
8. Deep understanding of responsible AI practices and model governance frameworks.