Engineering Manager — ML Model Evaluation & Quality

Apple, Inc.; Cupertino (CA); On-site; USD 206,000 - 356,000; Full time

Job summary

Apple Inc. in Cupertino, California, is seeking an Engineering Manager to lead the Model & Algorithm Evaluation & Quality team within Sensing & Connectivity.

You will oversee evaluation of location context ML models and the quality engineering that ships these features across iOS/watchOS, partnering with hardware to software teams. You will define evaluation strategies, build automation and dashboards, and guide a team through research-to-production quality gates while driving end-to-end product

Qualifications

• BS, MS, or PhD in Computer Science / Electrical Engineering or equivalent.
• 5+ years of relevant industry experience.
• 2+ years leading and managing an engineering team.
• Experience evaluating AI/ML models: benchmarks and evaluation protocols.
• Proficient in designing AI-assisted workflows using GenAI.

Responsibilities

• Own the model evaluation strategy for ML models and algorithms, incl. benchmarks and data validation.
• Set direction for evaluating models and translate assessments into improvements.
• Lead automation, CI, analytics, and monitoring to qualify features across releases.
• Identify KPIs, build dashboards, and present results to reviews and execs.
• Drive bug resolution and coordinate with Apple and partner teams to maintain quality.
• Collaborate with hardware, software, PM, and cross-functional partners for end-to-end quality.
• Hire, coach, and grow the team with career development.

Skills

ML model evaluation

Benchmarks design

Statistical analysis

GenAI testing

CI automation

Education

BS/MS/PhD in CS/EE

Tools

Python

CI/CD tooling

Job description

Apple Inc. in Cupertino, California, is seeking an Engineering Manager to lead the Model & Algorithm Evaluation & Quality team within Sensing & Connectivity.

You will oversee evaluation of location context ML models and the quality engineering that ships these features across iOS/watchOS, partnering with hardware to software teams. You will define evaluation strategies, build automation and dashboards, and guide a team through research-to-production quality gates while driving end-to-end product