Senior Machine Learning Infrastructure Engineer

Apple Inc

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Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$150,400–$277,600 / yr
Posted
3 days ago
Freshness
Confirmed live today

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $229k
This role $214k
$132k most similar roles pay here $319k

This role pays less than 62% of similar roles. Most pay $202,800–$254,750 — the shaded band above. At the midpoint, this role pays about $214k versus about $229k 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 2321 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1891 roles with salary data.

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At a glance

TL;DR · Senior Machine Learning Infrastructure Engineer

AIML - Senior Machine Learning Infrastructure Engineer -ML Compute, ML Platform & Technology joins the ML Compute team to build and maintain compute infrastructure for training, inferencing, and fine-tuning workloads. The role involves scoping, architecting, and delivering high-quality solutions while collaborating with internal teams to address challenges related to stability, reliability, efficiency, and cost-effectiveness in large-scale systems. Key responsibilities include communicating complex features, assessing industry trends, conducting code reviews, and mentoring new team members. Candidates will utilize Go and Python to develop backend systems for machine learning models. Required technical expertise includes distributed systems, containerization, and cloud platforms such as Kubernetes, Ray, Beam, and Flink. Preferred skills involve debugging accelerators like GPU, TPU, and AWS Trainium, alongside experience with frameworks including JAX, TensorFlow, PyTorch, TensorRT, and vLLM to solve complex infrastructure problems.

What you'll do

  • Architect and deliver high-quality solutions for large-scale machine learning compute workloads.
  • Develop infrastructure to support ML training, inference, and fine-tuning processes.
  • Optimize ML workloads to improve stability, reliability, efficiency, and cost-effectiveness.
  • Write production code using Go and Python to build scalable backend systems.
  • Manage and debug hardware accelerators such as GPUs, TPUs, and AWS Trainium.
  • Implement distributed systems using technologies like Kubernetes, Ray, Beam, and Flink.
  • Conduct code reviews and provide technical mentorship to onboard new team members.
  • Evaluate industry trends to identify and develop new technologies for the ML platform.

What we're looking for

  • Bachelor's degree in Computer Science, engineering, or a related field.
  • Advanced degrees in Computer Science, engineering, or a related field (preferred).
  • 4+ years of experience building scalable backend systems for training and evaluation of machine learning/deep learning models.
  • Proficiency in programming languages such as Python or Go.
  • Expertise in distributed systems, reliability, scalability, containerization, and cloud platforms.
  • Proficiency in cloud computing and data processing infrastructure tools including Kubernetes, Ray, Beam, and Flink.
  • Proficiency in working with and debugging accelerators like GPU, TPU, and AWS Trainium (preferred).
  • Proficiency in ML training and deployment frameworks such as JAX, TensorFlow, PyTorch, TensorRT, or vLLM (preferred).

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