Lead Machine Learning Engineer, Human Sensing
appleSeattle (WA)
Lead Machine Learning Engineer, Human Sensing
Posted today
appleSeattle (WA)
SENIORITY
Manager
About the role
Overview:
In this role you lead technical direction for the Human Sensing team, shaping ML programs from product goals to data strategy and evaluation. You partner with engineering leadership to set KPIs, scope projects, and ensure cross-functional alignment. You’ll drive on-device performance optimizations and own the evaluation framework to ensure robust, high-fidelity identity recognition and human perception models. You’ll work within a fast-evolving Applied Research organization that builds foundation models for facial and full-body perception across Apple experiences. This is a hands-on leadership position with a strong impact on product features and system performance. Compensation / Benefits Comprehensive medical and dental coverage Retirement benefits Employee stock programs Discounted products and free services Tuition reimbursement for education Potential discretionary bonuses or relocation assistance
Responsibilities:
Translate product ambitions into crisp ML programs with milestones Define KPI targets and data strategy including dataset requirements and collection protocols Design and lead comprehensive evaluation protocols and diagnostics to isolate failure modes Coordinate cross-functional efforts with Data, Evaluation, and Platform Integration teams Mentor engineers, ensure rapid execution, and maintain codebase health through reviews Dive deep into failure analysis and drive on-device model optimization
Key requirements:
Master’s or Ph.D. in Computer Science, Computer Engineering, or related field (or equivalent practical experience) with 6+ years of industry experience in CV and ML Technical lead or staff-level experience driving cross-functional initiatives Strong experience evaluating complex ML systems, benchmarking, and failure analysis Proven ability to coordinate teams, mentor peers, and align with management on roadmap execution High attention to detail, ownership mindset, and agility in fast-evolving research environments Proficiency in Python and PyTorch with hands-on experience maintaining shared repositories cross-functional collaboration mentorship and coaching ownership and accountability Python PyTorch on-device ML optimization (quantization-aware training, knowledge distillation, Core ML)
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