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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 seeks a Lead Machine Learning Engineer (Technical Lead) to set technical direction for a multimodal Human Sensing group in Seattle.

Responsibilities

Serve as the primary technical lead with engineering management 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 in collaboration with the Data team to reduce blind spots
Architect and lead the team’s evaluation framework and benchmarking pipelines, including custom metrics, evaluation scripts, and automated stress-testing tools
Lead failure mode analysis, root-cause investigation, and edge-case discovery to drive targeted model and data iterations
Coordinate day-to-day technical execution across multiple teams, including Evaluation, Integration, and Data Operations
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 to unblock research or validate hypotheses
Maintain the team’s core codebase: author and review PRs, uphold engineering hygiene, and support rapid iteration velocity
Communicate technical strategy, performance trade-offs, and progress to stakeholders and senior leadership; mentor junior and mid-level engineers
Stay current with machine learning and multimodal foundation model trends, plus best practices in 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: scoping projects, setting KPIs, and leading technical initiatives across cross-functional teams
Expertise in evaluating complex ML systems, defining benchmarking methodologies, and performing deep failure analysis
Experience coordinating engineering teams, mentoring peers, and partnering with management on roadmap execution
Strong attention to detail, ownership mindset, and agility in fast-evolving research environments
Deep proficiency in Python, PyTorch, and hands-on experience producing clean, maintainable code in 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
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
Discretionary restricted stock unit awards (eligible)
Discounted Apple stock purchase if voluntarily participating in the Employee Stock Purchase Plan

Preferred Qualifications

Deep domain knowledge in face recognition, identity re-identification (ReID), biometrics, or visual human sensing (pose, expression, human-object interaction)
Hands-on collaboration with Data Collection & Annotation teams to design robust 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 multi-modal 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 demonstrated through publications in top-tier journals or conferences, patents, or impactful software developments

Pay & Location

Location: Seattle, WA (onsite)
Base pay range: USD 175,000 - 308,500 per year
Base pay depends on skills, qualifications, experience, and location
Apple benefit, compensation, and employee stock program eligibility and terms apply

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