AIML - Staff ML Infrastructure Engineer, ML Platform & Technology - Pre-training Infrastructure
Apple
San Francisco, California
Posted today
Qualifications
Education
Bachelor's degree in Computer Science, Engineering, or a related field
Responsibilities
Primary Duties
- Drive performance optimization for large-scale foundation model training on TPUs, focusing on efficiency, throughput, and scalability
- Profile and optimize JAX/XLA workloads across compute, memory, communication, and compilation.
- Develop and optimize high-performance TPU kernels for critical ML operations such as attention and Mixture-of-Experts (MoE)
- Optimize distributed training techniques, sharding strategies, and collective communication over TPU interconnects (ICI/Fabric)
- Research and implement new techniques across the JAX, XLA, and TPU stack to improve end-to-end training performance
- Develop performance profiling, benchmarking, and automated tuning capabilities for large-scale training workloads.
- Collaborate with cross-functional engineers to solve large-scale ML training challenges
- Lead complex technical projects and mentor engineers in areas of your expertise
- Cultivate a team centered on collaboration, technical excellence, and innovation
Experience Requirements
Required
6+ years of experience building or optimizing high-performance ML or distributed systems
6 years of experience
Required Skills
Technical Skills
Proficient in Python or other relevant programming languagesStrong understanding of distributed systemsParallel computingPerformance optimizationExperience profiling and optimizing compute-, memory-, or communication-intensive workloads
Soft Skills
Ability to clearly communicate complex technical problems
Full Job Description
AIML - Staff ML Infrastructure Engineer, ML Platform & Technology - Pre-training Infrastructure
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!
As an engineer on the ML Compute team, your work will include:
Minimum Qualifications:
Preferred Qualifications:
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!
As an engineer on the ML Compute team, your work will include:
- Drive performance optimization for large-scale foundation model training on TPUs, focusing on efficiency, throughput, and scalability
- Profile and optimize JAX/XLA workloads across compute, memory, communication, and compilation.
- Develop and optimize high-performance TPU kernels for critical ML operations such as attention and Mixture-of-Experts (MoE)
- Optimize distributed training techniques, sharding strategies, and collective communication over TPU interconnects (ICI/Fabric)
- Research and implement new techniques across the JAX, XLA, and TPU stack to improve end-to-end training performance
- Develop performance profiling, benchmarking, and automated tuning capabilities for large-scale training workloads.
- Collaborate with cross-functional engineers to solve large-scale ML training challenges
- Lead complex technical projects and mentor engineers in areas of your expertise
- Cultivate a team centered on collaboration, technical excellence, and innovation
Minimum Qualifications:
- 6+ years of experience building or optimizing high-performance ML or distributed systems
- Proficient in Python or other relevant programming languages
- Strong understanding of distributed systems, parallel computing, and performance optimization
- Experience profiling and optimizing compute-, memory-, or communication-intensive workloads
- Ability to clearly communicate complex technical problems and collaborate with partners to develop solutions
- Bachelor's degree in Computer Science, Engineering, or a related field
Preferred Qualifications:
- Advanced degree in Computer Science, Engineering, or a related field
- Experience with accelerators such as TPU or GPU and understanding of accelerator architecture and performance characteristics
- Experience with JAX, XLA, PyTorch or other ML compiler/runtime stacks
- Experience developing or optimizing accelerator kernels using Pallas, Triton, CUDA, or similar technologies
- Experience optimizing large-scale foundation model training and distributed communication
How to Apply
Apple
About
Founded in 1976 by Steve Jobs, Steve Wozniak, and Ronald Wayne, Apple revolutionized personal computing and consumer electronics. Its iconic products include the iPhone, MacBook, and Apple Watch. Appl...
$206
/ hour
Apple pays $206 for Software Engineer in San Francisco, California, with most salaries ranging from $140 to $315. Pay can vary based on role, experience, and local cost of living.
Median
$206
Low
$140
High
$315
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