Machine Learning Research Engineer (Fitness Intelligence)

Quick Facts

• Role: Machine Learning Research Engineer (Fitness Intelligence – Watch Software)

• Focus: Applied machine learning for fitness experiences on Apple Watch and iPhone

• Output: Shippable, production-quality intelligence delivered through datasets, evaluations, model adaptations, and Swift client code

Description

You’ll be a senior technical leader in a small, deeply technical team at the intersection of applied machine learning and fitness. You’ll build and ship intelligence behind Apple’s fitness features by creating datasets, evaluations, prompt/tool definitions, model adaptations, and production client code that runs on device and server environments. You’ll also develop tooling and evaluation harnesses so engineers can build and validate intelligence-backed features with confidence.

Responsibilities

• Partner with feature-owning teams to define what the intelligence layer must deliver and co-own outcomes

• Write production client software in Swift, including APIs, on-device inference integration, and feature logic within real performance, power, and memory budgets

• Own the iteration loop to shipping quality (prompt development, tools/functions definitions, scenarios, and model adaptation)

• Design golden datasets, metrics, and evaluation pipelines to determine ship-readiness

• Bridge offline evaluation and production inference so measurements match user experience

• Drive scaling of techniques and infrastructure for broader rollout (languages/regions, feature awareness, interactivity)

• Track the state of the art via prototyping and evidence-based decisions on what is ready to ship

• Raise the technical bar through design reviews, mentorship, and clear written communication

• Design with user privacy from the first sketch

Requirements

• 8+ years industry experience, or PhD in machine learning/related field plus 5+ years industry experience

• Demonstrated experience shipping user-facing ML features to production quality

• Deep hands-on experience with large language models (prompting, fine-tuning, or adaptation)

• Strong evaluation methodology: dataset design, metric development, human and automated evaluation, and limits of each

• Strong software engineering skills in a compiled language and/or proficiency in Python with modern ML stack (e.g., PyTorch or JAX)

• Strong product sense balancing technical ambition, feasibility, and user experience

• Excellent communication skills for explaining technical tradeoffs

Benefits

• Lead applied ML work that directly powers user-facing fitness intelligence shipped to Apple Watch and iPhone

• Work in a small, deeply technical team with cross-functional collaboration across fitness, Siri, and platform intelligence

• Build privacy-first solutions with a high bar for quality and evidence-based shipping decisions