Machine Learning Research Engineer, Fitness Intelligence – Watch Software

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The Apple Watch Software team is looking for an exceptional machine learning engineer to help ship the intelligence behind Apple’s fitness experiences. You’ll take promising model capabilities from first prototype all the way to features on Apple Watch and iPhone. That means building the datasets, evaluations, prompts and model adaptations that get a capability to shipping quality, and writing the production client code that delivers it to users. You’ll work closely with the other fitness teams to bring unified intelligence capabilities to features across the platform, and you’ll help set the technical direction for a new and fast-moving domain. This role requires a passion for iteration, a high bar for quality, and a drive to see ideas all the way into shipping software. We value communication skills, integrity and creativity, and aspire to build diverse, balanced and dynamic teams.

n this role you’ll be a senior technical leader in a small, deeply technical team working where applied machine learning meets fitness. You’ll write production Swift that ships in the OS and runs both on device and in server-side environments. You’ll also build the evaluations, datasets and model improvements that make those features good. You’ll work closely with the Activity, Workout and Fitness+ engineering teams, as well as with Siri and platform intelligence teams across Apple. You’ll also help build the tools and harnesses that let engineers across the organization develop and evaluate intelligence-backed features with confidence.

Minimum Qualifications

8+ years of industry experience, or a PhD in machine learning or a related field plus 5+ years of industry experience.
A track record of shipping user-facing features built on machine learning, carried through the iteration needed to reach production quality.
Deep, hands-on experience with large language models, including prompting, fine-tuning or adaptation.
Strong command of evaluation methodology: dataset design, metric development, human and automated evaluation, and understanding the limits of each.
Strong software engineering skills in a compiled language and/or proficiency in Python and the modern ML stack (e.g. PyTorch or JAX).
Strong product sense and the ability to balance technical ambition, feasibility and user experience.
Excellent communication skills, including the ability to explain technical tradeoffs clearly to engineering and product partners.

Preferred Qualifications

Experience shipping production Swift, including API design and performance and memory budgets.
Experience deploying models on device, including quantization, compression or latency optimization.
Experience building datasets and measurement systems, and using them to make quality tradeoffs defensible.
A track record of influencing outcomes across organizational boundaries and delivering work that other teams’ features depend on.
Experience with time-series, sensor or multimodal data, especially from wearables.
Background in health, fitness or another domain where user trust and data sensitivity shape the design.
Familiarity with privacy-preserving machine learning techniques.
Publications at leading ML venues, or equivalent impact in industry.