AIML - Sr Machine Learning Engineer, Evaluation

Benefits

Parental leave

Not verified

Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

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Learning budget

Not verified

Verification

Not verified checked Jun 13, 2026

Salary

$212K-$386K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

157% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

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Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

AIML - Sr Machine Learning Engineer, Evaluation Cupertino, United States of America We are seeking a highly skilled and experienced machine learning engineer to join AIML Evaluation to build the systems that evaluate and refine Apple's foundation models and agents. As a key member of the team, you will help design and develop benchmarks, evaluators, simulation environments, and prompt and context optimization pipelines that drive quality improvements across Apple's AI experiences. You will collaborate with product teams and the foundation model team to close the loop between observation and improvement, contributing datasets, environments, and reward signals that drive model and agent quality. Our team builds the benchmarks, environments, and tooling that power model and agent refinement, and turns observations into actionable opportunities for the next model and agent iteration. We work across the full spectrum of evaluation: offline benchmarks, device-in-the-loop simulation, and on-device observation in production. We develop LLM-as-judge evaluators, train reward models calibrated against human feedback, optimize prompts and context for agents, and contribute targeted datasets and reward signals to foundation model post-training. In this role, you will play a crucial role in designing and developing evaluation and refinement infrastructure that supports a broad range of AI products at Apple. You will work on agent and model evaluation across offline, device-in-the-loop, and on-device settings; build automated prompt and context optimization pipelines; and partner with product and research teams to translate failure analysis into measurable model and agent improvements. You will also have the opportunity to engage with product teams

Read the full description at jobs.apple.com. FewerJobs shows a preview and links to the original posting.