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: 140 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $223k

This role $214k

$135k $293k

below market most similar roles pay here above market

This role pays more than 53% of similar roles. Most pay $192,050–$254,750 — the blue band above. At the midpoint, this role pays about $214k versus about $223k for comparable roles.

Based on 240 similar postings.

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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 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

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

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The Machine Learning Engineer - AI & ML Evaluation Frameworks joins the Health Sensing Machine Learning Interpretability & Analytics team to ensure clinical rigor and contextual trust in health sensing features. You will architect large-scale evaluation frameworks to interrogate unimodal ML systems and multi-modal foundation models, including LLMs and diffusion models. Daily responsibilities involve performing failure analysis to detect clinical hallucinations, building synthetic data pipelines to protect user privacy, and developing data adaptors for asynchronous time-series signals from wearables and cameras. You will use Python to write production-grade code and utilize tools like Spark, Kubernetes, and Airflow. Your work focuses on discovering biases, measuring demographic equity, and providing actionable engineering insights to improve the safety and reliability of digital health products.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

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Skills

Python LLMs Diffusion Models GenAI CI/CD Git Spark Kubernetes Airflow RAG Federated Learning Synthetic Data Generation Model Interpretability Failure Analysis OOP

What you'll do

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

What we're looking for

BS in Computer Science, Machine Learning, Statistics, or a related field.
MS/PhD in Computer Science, Machine Learning, Statistics, or a related field (preferred).
3+ years of experience in ML Engineering or Applied ML.
Strong experience evaluating supervised, unsupervised, LLMs, and deep learning models.
Proficiency in Python with the ability to write production-grade code using OOP, CI/CD, and Git.
Hands-on experience in failure analysis, evaluating LLMs, and driving model improvements.
Experience building data pipelines, inference frameworks, and automated evaluation systems.
Experience with synthetic data generation, parallel data processing, or AI Safety (preferred).

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