AIML - Sr Machine Learning Engineer, Evaluation

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$212,000–$386,300 / yr
Posted
4 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $224k
This role $299k
$146k most similar roles pay here $412k

This role pays more than 97% of similar roles. Most pay $197,925–$249,750 — the shaded band above. At the midpoint, this role pays about $299k versus about $224k 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 1777 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1443 roles with salary data.

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At a glance

TL;DR · AIML - Sr Machine Learning Engineer, Evaluation

Join our AIML Evaluation team as a Senior Machine Learning Engineer to design and develop evaluation infrastructure for Apple's foundation models and agents. You will create benchmarks, evaluators, simulation environments, and prompt optimization pipelines that enhance AI product quality across various settings including offline, device-in-the-loop, and on-device evaluations. Collaborate with product teams to identify and address quality gaps by contributing datasets, reward signals, and environments to the post-training loop. Essential skills include a strong background in machine learning systems, distributed infrastructure, and experience with ML frameworks like PyTorch. Ideal candidates have expertise in LLM evaluation, reward modeling, prompt optimization, and agentic systems, as well as proficiency in Python and problem-solving across multiple codebases and teams.

What you'll do

  • Design and build evaluation infrastructure for agents and foundation models.
  • Develop LLM judges, reward models, and prompt optimization pipelines.
  • Build simulation environments for agent evaluation and trajectory-based data generation.
  • Collaborate with product teams to identify and address quality gaps in AI products.
  • Contribute datasets, environments, and reward signals to the post-training loop of foundation models.
  • Work on agent and model evaluation across offline, device-in-the-loop, and on-device settings.

What we're looking for

  • Strong background in machine learning and distributed systems.
  • 8+ years of professional experience as a software engineer in machine learning or related field.
  • Experience building and maintaining ML infrastructure for evaluation, training, or deployment.
  • Ability to work effectively across multiple codebases, teams, and organizations.
  • Proven track record in LLM evaluation, reward modeling, prompt optimization, or agentic systems.

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