About this role
Summary: The Fitness Sensing AI/ML Lead drives technical direction for fitness sensing by building AI/ML models and agentic workflows that convert sensor data into actionable insights. This role involves hands-on modeling, product definition, and cross-functional leadership to ship features impacting millions of users daily.
Every day, millions of people check their iPhone and Apple Watch to understand their fitness — how hard they trained, how ready they are to go, how their body is adapting over time. The Fitness team within Applied Sensing & Health builds the AI and sensing technology behind that understanding. We apply foundation models, including large language models, and agentic AI workflows to motion, heart, and behavioral sensor data, turning raw signals into insights people can trust and act on every single day. This work has shipped as Readiness, Cardio Fitness, including the new Step Test Movement Evaluation, best-in-class Pedometer Step Counting, and many more.
We are a dynamic, collaborative group working at the intersection of scientific research, product development, and systems engineering. We build best-in-class AI/ML models, including the integration, adaptation, and tuning of foundation models on multimodal sensor data, and the agentic workflows that accelerate how we build and validate them. We're looking for a deeply technical, passionate leader to help set the technical direction for fitness sensing. The right person is equally at home as a hands-on senior contributor and as a mentor and informal lead for other scientists and engineers. If this is you, we'd love to hear from you.
Description
As a senior technical lead on the Fitness team, you will drive the technical direction for fitness sensing — building AI/ML models, including foundation models and agentic workflows, that turn sensor data into fitness insights millions of people rely on every day. You'll move fluidly between hands-on modeling, product definition, and cross-functional leadership, while mentoring other engineers and scientists, including senior-level peers. Most importantly, you'll ship features that impact millions of users daily, bringing creativity, initiative, and a personal stake in the product you build.
Responsibilities
Designing and implementing AI/ML models, including foundation models applied to multimodal sensor data, for Health and Fitness use cases, driving end-to-end performance and failure analysis
Evaluating and deploying AI agents and agentic workflows to augment and accelerate how the team builds, tests, and validates models
Designing and supporting user study data collections for model development and validation
Architecting and modernizing core components of a large, established fitness algorithm and software stack, balancing near-term delivery with long-term maintainability
Partnering on product definition — translating health and fitness concepts into clear, well-scoped features, and acting as the first user of your own work
Leading cross-functional collaboration across design, hardware sensing, QE, and project management throughout the software lifecycle
Providing technical mentorship and informal leadership to other engineers and scientists on the team, including senior-level peers
Most importantly, you will help ship interactive features that impact millions of users on a daily basis. You take responsibility; you demonstrate creativity, initiative, and the ability to work to deadlines. You feel a personal stake in the product you ship. You thrive in uncertainty and strive to bring order to it. You keep your eye on the ball; you build strong relationships; and you are constantly looking to improve yourself and your team.
Minimum qualifications
MS or PhD in a quantitative modeling and data science discipline such as machine learning, computer science, statistics/biostatistics, or similar
10+ years of relevant industry experience, including experience mentoring, informally leading, or managing other engineers/scientists
Strong background in developing deep learning and/or foundation models for health or fitness applications, with experience across multiple data modalities (time series, sensor data, etc.)
Hands-on experience with LLMs and agentic AI systems, including evaluating or deploying AI agents to augment engineering or research workflows
Demonstrated experience taking models from research through to shipped, production features, including performance and failure analysis, in the health or fitness space
Strong working knowledge of Python and running experiments with data at scale
Preferred qualifications
Prior people management experience, or a track record as a technical lead with strong management instincts — this role involves significant cross-functional work and mentorship of senior scientists and engineers
Experience developing generative AI systems, such as large language models, in an applied setting, including post-training techniques like fine-tuning, adapter training, or reinforcement learning from human feedback
Experience with embedded or resource-constrained systems (power, memory, performance optimization)
Working knowledge of Swift, SwiftUI, C++, or Objective-C
Strong product instincts — passion for product definition, user experience, and being the first user for your own features
Excellent interpersonal and communication skills (written and verbal); experience working across cross-functional and interdisciplinary teams