Lead, Foundation Model Data & Evaluation

Apple, Inc.; Cupertino (CA); On-site; USD 216,000 - 325,000; Full time

Benefits offered by this job

Employee stock programs

Discretionary bonuses / commissions

Relocation assistance

Educational expense reimbursement

Comprehensive health coverage

Job summary

Apple, Inc. in Cupertino, CA, is seeking skilled Machine Learning Engineers to transform cutting-edge research into scalable, production-ready AI solutions.

You will lead data curation, evaluation, and training strategies across the foundation model lifecycle, influencing model quality and user experience on Apple devices. You are a recognized technical expert who mentors teams, defines standards, and drives adoption of shared systems while ensuring privacy and compliance.

Qualifications

• PhD with 5+ years or MS with 8+ years of experience in machine learning or data infrastructure, including leading technical work at scale.
• Deep machine learning expertise in LLMs or multimodal foundation models, with depth in either evaluation methodology or large-scale training data systems and curation, and working fluency in the other.
• Strong fundamentals in statistics and experimental design, and the credibility to review designs and experiments in detail.
• A track record of training data or evaluation work on large models that measurably improved model quality or changed how models are built.
• Technical leadership across teams: setting direction, mentoring senior engineers or researchers, and driving adoption of systems, benchmarks, or standards beyond your own team.
• Hands-on proficiency in Python and an ML framework such as PyTorch or JAX.

Responsibilities

• Shape strategy for training data and evaluation across pre-training, mid-training, and post-training, aligned with the production model roadmap.
• Help decide where to invest across data acquisition, curation, synthetic data, and evaluation coverage, including what to build, buy, or source from vendors.
• Set standards that other teams adopt for benchmark governance, release gating, contamination, and data documentation.
• Turn evaluation failures into data decisions: decide which capability gaps to close through acquisition, curation, or synthetic generation, and verify the result.
• Lead data ablations and scaling-law studies, and define how data mixture decisions are made and validated.
• Lead decontamination across pre-training, mid-training, and post-training data, including synthetic and vendor data. Define the standard, measure residual contamination, and protect held-out evaluation sets from overuse.
• Define the evaluation portfolio for reasoning, coding, knowledge, and multi-turn agentic workflows, and decide where to build new benchmarks and where to adopt existing ones.
• Lead model-based judging, including how judges are validated, versioned, and checked for bias.
• Build product-aligned evaluation that predicts user-perceived quality on Apple devices, and partner with annotation teams and vendors to correlate automated metrics with human judgment.
• Direct the architecture of high-throughput systems that acquire, process, and curate petabytes of text, code, and multimodal data across cloud and high-performance compute.
• Set the quality bar for algorithmic data curation, including semantic deduplication, heuristic and model-based quality filtering, and synthetic data generation.
• Drive data provenance, licensing, privacy, and takedown practices for training data with security, legal, and compliance teams.
• Raise the technical bar across data and evaluation through design reviews, mentoring, and hiring, and drive adoption of shared systems and tooling across teams.
• Where the role includes a team, manage and grow it.
• Communicate findings, risks, and recommendations clearly to senior leadership and cross-functional partners.

Skills

Python

Statistics

Experimental design

LLMs / Multimodal ML

Education

PhD

MS

Tools

PyTorch

JAX

Job description

Apple, Inc. in Cupertino, CA, is seeking skilled Machine Learning Engineers to transform cutting-edge research into scalable, production-ready AI solutions.

You will lead data curation, evaluation, and training strategies across the foundation model lifecycle, influencing model quality and user experience on Apple devices. You are a recognized technical expert who mentors teams, defines standards, and drives adoption of shared systems while ensuring privacy and compliance.