GPU ML Engineer Job ID- 1454 Job ID- 3742

MaziCTools; Los Angeles (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Apple in Cambridge, Massachusetts seeks extraordinary machine learning and GPU programming engineers to provide robust compute solutions for accelerating ML networks on Apple Silicon.

The role offers opportunities to influence design of compute and programming models in next-generation GPU architectures and to contribute to ML training acceleration technologies across multiple platforms.

Qualifications

• Strong programming and problem-solving skills.
• Solid understanding of machine learning fundamentals.
• Knowledge of GPU compute programming models and optimization techniques.
• Experience with GPU compute framework development and optimization.
• Experience with ML frameworks (TensorFlow, PyTorch or JAX).

Responsibilities

• Develop ML training acceleration techniques for GPU.
• Implement/optimize APIs in ML frameworks and Graph APIs.
• Tune GPU-accelerated training across products.
• Analyze performance and optimize compiler/kernel code.
• Support adoption of GPU-accelerated training across clients.

Skills

Programming

Machine learning basics

GPU compute

API development

ML frameworks

Tools

LLVM/MLIR

Metal API

Job description

Cambridge, Massachusetts, United States

Summary

Posted: Sep 11, 2024

Weekly Hours: 40

Apple’s Compute Frameworks team in GPU, Graphics and Displays org provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple for iOS, macOS and Apple TV. Our efforts are currently focused in the key areas of linear algebra, image processing, machine learning, along with other projects of key interest to Apple. We are always looking for exceptionally dedicated individuals to grow our outstanding team.

Description

Our team is seeking extraordinary machine learning and GPU programming engineers who are passionate about providing robust compute solutions for accelerating machine learning networks on Apple Silicon. Role has the opportunity to influence the design of compute and programming models in next generation GPU architectures.

• * Adding optimizations in machine learning computation graph.
• * Defining and implementing APIs in Metal Performance Shaders Graph, investigating new algorithms.
• * Develop/maintain/optimize ML training acceleration technologies.
• * Support adoption of GPU-accelerated training across 1st and 3rd party clients.
• * Tune GPU-accelerated training across products.
• * Performing in-depth analysis, compiler and kernel level optimizations to ensure the best possible performance across hardware families.

Intended deliverables

• * ML training GPU acceleration technology.
• * Optimized ML training across products.

Minimum Qualifications

• Proven programming and problem-solving skills.
• Good understanding of machine learning fundamentals.
• GPU compute programming models & optimization techniques.
• GPU compute framework development, maintenance, and optimization.
• Machine learning development using one or more ML frameworks (TensorFlow, PyTorch or JAX).

Preferred Qualifications

• Experience with adding computational graph support, runtime or device backend to Machine learning libraries (TensorFlow, PyTorch or JAX) support is a plus.
• Experience with high performance parallel programming, GPU programming or LLVM/MLIR compiler infrastructure is a plus.
• Experience with system level programming and computer architecture.
• Background in mathematics, including linear algebra and numerical methods.

GPU ML Engineer Job ID- 1454 GPU ML Engineer Job ID- 1454 Job ID- 3742