Engineering Program Manager – Machine Learning Features

Summary
Play a part in shaping the future of human-computer interaction. We're looking for an Engineering Program Manager (EPM) to turn advanced machine learning in speech, audio and computer vision into features that ship to customers.

You'll work across ML research, data collection, silicon, FW, and the device and companion SW teams that bring these features to Apple customers.Your work will cover every stage, from the first dataset to the final release.

Description
You'll own the plan for taking ML features from research to release. That covers data planning, model training and evaluation, optimization for Apple silicon, integration with SW teams, and release. You'll keep teams aligned, make risk visible early, and help leadership decide when model quality, performance and schedule pull in different directions. You'll be comfortable with how uncertain research is, and disciplined about delivering what ships.

Responsibilities

• Own the delivery plan for ML features, from research and prototyping through integration, validation and release
• Partner with data teams to build the data strategy and plan, making sure it covers what the models need and supports program milestones: what data, at what scale and coverage, and by when
• Align model milestones with HW builds, pre-silicon validation (simulation and FPGA), and silicon bring-up, ensuring models are ready at each gate
• Lead integration with SW groups, including model handoff, interfaces, integration schedules and release timing
• Align ML teams, MLOps and data science on priorities, compute capacity and dependencies
• Track model quality, latency, memory and power against product targets, and lead trade-off decisions
• Set up model release practices: readiness gates, versioning, regression tracking and post-integration monitoring
• Summarize ML progress into clear, data-driven recommendations for leadership.
  
  

• B.Sc. in Computer Science, Electrical Engineering, or a related STEM field
• 8+ years of relevant experience, including significant engineering program management experience in SW or ML development
• Hands-on background as an ML engineer, researcher or data scientist
• SW Experience working with data teams to define data strategy and plans for ML programs, with a clear understanding of how data drives model quality
• Solid understanding of the ML lifecycle, with the technical depth to engage credibly with researchers and engineers
• Experience with HW NPI cycles (prototype builds, pre-silicon validation)
• Using AI tools in daily work to improve productivity
• Excellent communication skills, including summarizing complex status for executive audiences
• Experience leading through influence in a matrixed, multinational environment
  
  

• M.Sc. or Ph.D. in a related field
• Experience with speech, audio or computer vision ML (e.g., ASR, voice isolation, video restoration)
• Familiarity with large-scale data collection and annotation practices, including privacy considerations
• Experience with on-device ML and optimization for dedicated HW or neural engines
• Familiarity with MLOps practices: data pipelines, distributed GPU training, CI/CD for models
• Experience with platform SW release processes and working with US-based teams
• Comfortable with ambiguity, using AI tools in daily work, and calm under pressure