ML Research Engineer, AI Evaluation Platform

Apple Inc

Quick summary

Work type: On-site
Location: Seattle, WA
Salary: $171,600–$258,100 / yr
Posted: 63 days ago
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $214k

This role $215k

$160k most similar roles pay here $269k

This role pays more than 58% of similar roles. Most pay $182,721–$246,150 — the shaded band above. At the midpoint, this role pays about $215k versus about $214k 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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · ML Research Engineer, AI Evaluation Platform

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As an ML Research Engineer on Apple’s AI Evaluation Platform team within Services Engineering, you will bridge the gap between research and production by rapidly prototyping evaluation methods and scaling them to robust, cloud-based services. Your day-to-day involves collaborating with scientists to implement cutting-edge techniques from recent papers, designing scalable experiment infrastructure, and working closely with platform engineers to deploy these solutions in a production environment. You must have strong proficiency in Python and modern ML frameworks like PyTorch or TensorFlow, along with experience in cloud-native development and deployment using Docker, Kubernetes, and CI/CD pipelines. This role requires expertise in large language models and the ability to work effectively in an interdisciplinary team focused on advancing AI evaluation methodologies at scale for Apple’s expansive user base.

Skills

Python PyTorch JAX TensorFlow Docker Kubernetes CI/CD Ray Spark DeepEval Ragas TruLens LangSmith Git PyTest

What you'll do

Rapidly prototype new AI evaluation methods based on recent research papers.
Refactor experimental code into production-ready Python packages for scalable deployment.
Design and maintain infrastructure to run large-scale evaluation experiments efficiently.
Provide critical technical feedback to researchers on feasibility and scalability issues.
Identify and engineer solutions to scale evaluation workflows at enterprise level.
Champion engineering best practices in the research workflow, ensuring high code quality.

What we're looking for

Bachelor's degree in Computer Science, Machine Learning, Software Engineering, or related field (Master’s preferred)
2+ years of hands-on experience combining machine learning and software engineering
Strong proficiency in Python and modern ML frameworks like PyTorch, JAX, TensorFlow
Experience working with large language models and implementing complex methods from recent papers
Demonstrated ability to move experimental code from prototype to production-ready systems
Practical experience with cloud-native development, including containerization and CI/CD pipelines
Strong communication skills for interdisciplinary team collaboration