Machine Learning Research Scientist - Health AIML

Apple Inc

Quick summary

Work type: On-site
Location: Seattle, WA
Salary: $201,300–$367,400 / yr
Posted: 99 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $217k

This role $284k

$148k most similar roles pay here $391k

This role pays more than 90% of similar roles. Most pay $183,733–$249,750 — the shaded band above. At the midpoint, this role pays about $284k versus about $217k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1792 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1453 roles with salary data.

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At a glance

TL;DR · Machine Learning Research Scientist - Health AIML

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The Machine Learning Research Scientist role at Apple’s Health AIML team involves leading research into multimodal models for health and fitness, focusing on developing foundational technology that scales globally. This senior position requires expertise in large-scale multimodal model development to enhance intelligent health experiences. Day-to-day responsibilities include designing new architectures, executing experiments, optimizing model performance, and contributing to infrastructure improvements. Candidates must have a PhD in a relevant field, industry experience, and contributions to major LLM training runs. Strong skills with deep learning frameworks like PyTorch, JAX, or TensorFlow are essential, along with experience in time-series modeling and self-supervised learning. The role aims to address real-world health challenges by deploying advanced AI technologies safely and effectively at scale.

Skills

PyTorch TensorFlow JAX Multimodal models Deep learning frameworks Time-series modeling Self-supervised learning Cross-modal training CI/CD Python AWS Kubernetes

What you'll do

Lead research into health and fitness representation models and multimodal models.
Design, prototype, and scale new architectures for improved model intelligence.
Execute and analyze experiments to enhance model performance independently.
Study, debug, and optimize computational efficiency of models.
Contribute to the development of training and inference infrastructure.

What we're looking for

PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field.
Industry experience with contributions to major large language model training runs.
Proven track record of publishing state-of-the-art research.
Strong skills with deep learning frameworks like PyTorch, JAX, TensorFlow.
Experience in training and evaluating multimodal models.

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