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Today

Lead Machine Learning Engineer, Human Sensing

Apple Seattle, WA

Seattle, WA

Today

$175k - $309k/yr Full time Manager Ai Ml Artificial Intelligence

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Job Description

Apple’s Human and Object Understanding (HOUr) team is hiring a Lead Machine Learning Engineer (Technical Lead) to set technical direction for a multimodal Human Sensing team in Seattle, WA.

Partner with engineering management as the primary technical lead to define project scope, technical milestones, and roadmap execution
Set KPI targets and quality benchmarks across demographics, environmental conditions, and device use cases
Define dataset collection, annotation, and curation strategy with the Data team to reduce model blind spots
Architect and lead the team’s evaluation framework and benchmarking pipelines (custom metrics, evaluation scripts, automated tooling)
Stress-test models against production scenarios through evaluation and benchmarking automation
Lead failure mode analysis: root-cause investigation and edge-case discovery to drive model and data iterations
Coordinate day-to-day technical execution across Evaluation, Integration, and Data Operations teams
Drive model optimization in partnership with integration and other partner teams
Train, fine-tune, and run experiments with state-of-the-art vision architectures when needed for research and hypothesis validation
Maintain the team’s core codebase: author and review PRs, uphold engineering hygiene, and enable rapid iteration velocity
Communicate technical strategy, performance trade-offs, and progress to stakeholders and senior leadership
Guide and mentor junior and mid-level engineers
Stay current with machine learning trends and best practices across multimodal foundation models, computer vision, and natural language understanding

Requirements

Master’s or Ph.D. in Computer Science, Computer Engineering, or related field (or equivalent practical experience)
6+ years of industry experience in Computer Vision and Machine Learning
Proven Technical Lead or Staff-level experience driving project scoping, KPI setting, and technical initiatives across cross-functional teams
Expertise in evaluating complex ML systems, defining benchmarking methodologies, and conducting deep-dive failure analysis
Ability to coordinate engineering teams and mentor peers while partnering closely with management on roadmap execution
Strong ownership mindset, attention to detail, and agility in fast-evolving research environments
Deep proficiency in Python and PyTorch, including hands-on experience writing clean, maintainable code and managing shared repositories

Technologies

Python, PyTorch
Core ML
Quantization-aware training, knowledge distillation
Latency profiling, quantization, pruning
Multimodal foundation models, computer vision, natural language understanding
Face recognition, identity re-identification (ReID)
Foundation vision models
Large-scale Vision-Language Models (VLMs), large language models (LLMs)
Multimodal large language models (LLMs), large-scale vision-language models (VLMs)

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Range of discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments (may be eligible)
Relocation (may be eligible)
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Eligible for discretionary restricted stock unit awards
Can purchase Apple stock at a discount with voluntary participation in the Employee Stock Purchase Plan

Preferred Qualifications

Domain knowledge in face recognition, identity re-identification (ReID), biometrics, or visual human sensing (pose, expression, human-object interaction)
Experience collaborating with Data Collection & Annotation teams on collection protocols and active learning datasets
Experience with on-device model optimization (quantization-aware training, knowledge distillation, Core ML conversion, latency profiling)
Experience with foundation vision models or large-scale Vision-Language Models (VLMs)
Hands-on experience training and scaling multimodal LLMs or large-scale VLMs
Experience with on-device ML, model optimization (knowledge distillation, quantization, pruning), or production-grade ML pipelines
Research and innovation background shown through publications, patents, or impactful software developments

Pay & Benefits

Base pay range: $175,000 to $308,500 per year
Base pay depends on skills, qualifications, experience, and location
Apple also offers eligibility for discretionary restricted stock unit awards and an Employee Stock Purchase Plan discount (if voluntarily participating)
Note: Benefits, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program

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