Machine Learning Engineer, AI & ML Evaluation Frameworks

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$150,400–$277,600 / yr
Posted
94 days ago
Freshness
Confirmed live yesterday

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $221k
This role $214k
$135k most similar roles pay here $293k

This role pays more than 53% of similar roles. Most pay $187,850–$254,750 — the shaded band above. At the midpoint, this role pays about $214k versus about $221k 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 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer, AI & ML Evaluation Frameworks

The Machine Learning Engineer - AI & ML Evaluation Frameworks joins the Health Sensing Machine Learning Interpretability & Analytics team to build scalable evaluation infrastructure and lead investigations into model performance. You will architect large-scale frameworks to interrogate unimodal systems and multi-modal foundation models, while performing failure analysis to identify reasoning flaws and clinical hallucinations. Your daily work involves developing synthetic data pipelines for training without exposing user data, building data adaptors for asynchronous time-series signals, and creating tools to measure demographic equity. You will utilize Python, Git, CI/CD, Spark, Kubernetes, and Airflow to solve problems related to AI safety and model interpretability. The role focuses on ensuring clinical rigor and safety within health features by evaluating LLMs, diffusion models, and multi-modal sensor fusion while maintaining strict privacy standards across diverse populations.

What does a Machine Learning Engineer earn in California?

Median $246394 from 172 postings across 28 companies.

See salary data

What you'll do

  • Design scalable evaluation frameworks to assess the performance and safety of traditional ML and foundation models.
  • Conduct deep-dive failure analyses to identify clinical hallucinations, reasoning flaws, and edge cases.
  • Build synthetic data generation pipelines to enable model training without exposing real user data.
  • Develop data adapters and visualizers to fuse asynchronous time-series signals from wearables and cameras.
  • Create tools and metrics to detect biases and measure demographic equity across diverse populations.
  • Translate evaluation results into actionable engineering insights for researchers, algorithm leads, and clinical experts.

What we're looking for

  • Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field.
  • Master's or PhD in Computer Science, Machine Learning, or Statistics is preferred.
  • 3+ years of experience in Machine Learning Engineering or Applied ML.
  • Experience evaluating supervised, unsupervised, LLMs, and deep learning models.
  • Proficiency in Python with ability to write production-grade code using OOP, CI/CD, and Git.
  • Hands-on experience in failure analysis, LLM evaluation, and building data pipelines and inference frameworks.
  • Experience with synthetic data generation, prompt engineering, or privacy-preserving ML techniques.
  • Strong communication skills to explain complex technical concepts to both technical and non-technical audiences.

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