AIML - Sr Machine Learning Engineer, Data and ML Innovation

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$181,100–$318,400 / yr
Posted
7 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $217k
This role $250k
$143k most similar roles pay here $337k

This role pays more than 84% of similar roles. Most pay $188,537–$246,150 — the shaded band above. At the midpoint, this role pays about $250k versus about $217k 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, Data and ML Innovation

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Join our dynamic team as a Senior Machine Learning Engineer specializing in foundation model evaluation, where you will contribute to assessing and enhancing the performance of cutting-edge AI models that power Apple’s intelligent features. Your daily tasks include ensuring the stability and reliability of evaluation systems, designing innovative methodologies for measuring model capabilities, and developing tooling to streamline metrics generation and reporting. You will collaborate closely with ML researchers to refine model evaluations and drive improvements in future iterations. This role requires expertise in large language models, experience with LLM training and evaluation workflows, and a strong background in software engineering fundamentals such as debugging and production reliability. Ideal candidates have hands-on experience evaluating large-scale AI models and possess excellent communication skills alongside a relentless curiosity for innovation.

Skills

Python Java C++ TensorFlow PyTorch Kubernetes Docker AWS CI/CD Prometheus Grafana LLM_evaluation_workflows agentic_LLM_systems

What you'll do

  • Ensure stability, reliability, and performance of foundation model evaluation systems.
  • Design and implement novel methodologies for evaluating AI models.
  • Develop tooling to simplify metrics generation, ingestion, and reporting.
  • Collaborate with researchers on improving model hillclimbing techniques.
  • Utilize agentic LLM systems to enhance model evaluation processes.

What we're looking for

  • 5+ years of hands-on ML engineering experience, including at least 1 year on large language models or generative AI.
  • Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or related technical field.
  • Strong software engineering skills: debugging, testing, code reviews, and production reliability/scalability.
  • Experience with LLM training and evaluation workflows including pre-training, post-training, online/offline evaluations.
  • Ability to design and implement novel evaluation methodologies for ML models.

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