February 12, 2025

Machine Learning Engineer

Mid • On-site

$166,600 - $296,300/yr

San Diego, CA

Summary

Posted:
Role Number:200590536
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something.

Description

We are seeking an experienced Infrastructure Engineer to design and develop scalable infrastructure solutions for data centric machine learning workflows. This role involves building tools and systems that support large-scale data analysis, data visualization, and failure analysis of machine learning models and human annotations. The ideal candidate will have a strong background in cloud-based infrastructure, distributed computing, and LLM-serving frameworks, with expertise in building solutions for data processing at scale.

Minimum Qualifications

  • BS and a minimum of 10 years relevant industry experience
  • Strong background in computer science: algorithms, data structures and system design
  • 4+ year experience on large scale distributed system design, operation and optimization
  • Strong expertise in distributed systems, reliability and scalability, containerization, and cloud platforms
  • Proficient in cloud computing infrastructure and tools: Kubernetes, Ray, PySpark
  • Familiarity with one of the popular ML Frameworks like Pytorch, JAX or Tensorflow
  • Excellent interpersonal skills able to work independently as well as cross-functionally
  • MS or BS in Computer Science, Engineering, Mathematics, Statistics or a related field OR equivalent practical experience

Preferred Qualifications

  • Familiarity with end-to-end Machine Learning Lifecycle
  • Experience building data solutions to support machine learning, and experimentation workflows Knowledge of data processing pipelines for Machine Learning Models
  • Proficient in ML training and deployment frameworks, like: JAX, Tensorflow, PyTorch, TensorRT, vLLM

Pay & Benefits

  • At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $166,600 and $296,300, and your base pay will depend on your skills, qualifications, experience, and location.

    Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

    Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.