Apple
AIML - Staff ML Infrastructure Engineer, ML Platform & Technology - Pre-training Infrastructure
$185K–$325K
San Francisco Bay Area, California · Staff · Full-time · Posted Aug 31, 2026
- Experience
- 6+ years; no alternatives stated.
- Education
- Bachelor's degree in Computer Science, Engineering, or a related field; no equivalent-experience alternative stated.
About the job
Optimizes the performance and scalability of large-scale foundation model training on TPUs and leads related ML infrastructure projects.
What you'll do
- Profile and optimize JAX/XLA workloads, TPU kernels, distributed training, and communication.
- Build profiling, benchmarking, and automated tuning capabilities for large-scale training.
- Lead technical projects, mentor engineers, and collaborate across teams on ML training challenges.
What they ask for
- 6+ years of experience building or optimizing high-performance ML or distributed systems
- Proficiency in Python or other relevant programming languages
- Strong understanding of distributed systems, parallel computing, and performance optimization, with experience profiling and optimizing intensive workloads
- Bachelor's degree in Computer Science, Engineering, or a related field
Nice to have
- Advanced degree in Computer Science, Engineering, or a related field
- Experience with TPU/GPU accelerators, JAX, XLA, PyTorch, Pallas, Triton, CUDA, or large-scale foundation model training
Pay
$184,700 and $324,800 (base salary range)
Tools
TPU, JAX, XLA, Python, PyTorch, Pallas, Triton, CUDA
AI focus
Improves infrastructure and performance for large-scale foundation model pre-training, including accelerator kernels and distributed training.
Model-written summary · the original posting is authoritative