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AIML - Senior Machine Learning Engineering Manager, Evaluation

Reads like a Data Leadership role: running a data team.

Cupertino

Pay
Pay not listedSimilar roles state $153K–$225K
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Lead a small team working on model evaluation, agent optimization and data generation

  • Turn observed quality gaps into targeted improvements to prompts, harnesses, datasets and models

  • Move from research papers and experiments to production-quality ML pipelines

  • Mentor engineers and align teams around a clear technical direction

  • Build repeatable evaluation and refinement loops across Apple Foundation Models and product teams

From the employer’s posting
lead a small team working at the intersection of model evaluation, agent optimization, and data generation
turning observed quality gaps into targeted improvements to prompts, agent harnesses, datasets, and models
moving from research papers and experimental results to production-quality ML pipelines
mentoring engineers and aligning teams around a clear technical direction
creating repeatable evaluation and refinement loops that improve the quality of Apple intelligence experiences

What you’ll bring

All qualifications

Core experience

  • Technical depth in machine learning, hands-on engineering
  • Comfortable taking research results into production ML pipelines
  • People leadership and mentoring experience
Qualification wording
combine technical depth with people leadership
comfortable moving from research papers and experimental results to production-quality ML pipelines
while mentoring engineers and aligning teams around a clear technical direction

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Live
First seen by us
Aug 27, 2026 · 65 days ago
Recorded sightings
382
Last seen by us
Nov 1, 2026

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Job description

View original posting ↗

Apple's AIML Evaluation team builds the systems and methodologies that measure and improve the quality of foundation models and agentic experiences. We are looking for a senior, hands-on Machine Learning Engineering Manager to lead a small team working at the intersection of model evaluation, agent optimization, and data generation. In this role, you will help define how evaluation closes the loop with model and product development, turning observed quality gaps into targeted improvements to prompts, agent harnesses, datasets, and models. You will combine technical depth with people leadership. You should be comfortable moving from research papers and experimental results to production-quality ML pipelines, while mentoring engineers and aligning teams around a clear technical direction. Your work will span Apple Foundation Models and product teams, with the goal of creating repeatable evaluation and refinement loops that improve the quality of Apple intelligence experiences.
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Location & working pattern

Cupertino

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