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Machine Learning - Compiler Engineer II, AWS Neuron, Annapurna Labs

Amazon

Cupertino (CA)

On-site

USD 120,000 - 180,000

Full time

30+ days ago

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Job summary

Join a forward-thinking company at the forefront of the AI revolution, where you will play a pivotal role in developing the next generation Neuron compiler. This exciting position involves transforming machine learning models for deployment on cutting-edge AWS hardware, solving complex optimization problems, and collaborating with talented teams to deliver exceptional software solutions. You will have the opportunity to work with advanced technologies and contribute to the evolution of AI accessibility for developers worldwide. If you are passionate about software engineering and eager to make a significant impact, this role is perfect for you.

Qualifications

  • 3+ years of software development experience, including design and architecture.
  • Experience in object-oriented languages like C++ or Java is a must.

Responsibilities

  • Design, implement, and maintain innovative software solutions for Neuron compiler.
  • Collaborate with chip architects and ML teams to optimize performance.

Skills

C++
Java
Compiler Design
Machine Learning Frameworks
Object-Oriented Programming

Education

Bachelor's Degree in Computer Science
Master's Degree or PhD in Computer Science

Tools

OpenXLA
StableHLO
MLIR
LLVM
Bazel
CMake

Job description

Job ID: 2933964 | Amazon Web Services, Inc. - A97

Do you want to be part of AI revolution? At AWS our vision is to make deep learning pervasive for everyday developers and to democratize access to AI hardware and software infrastructure. In order to deliver on that vision, we’ve created innovative software and hardware solutions that make it possible. AWS Neuron is the SDK that optimizes the performance of complex ML models executed on AWS Inferentia and Trainium, our custom chips designed to accelerate deep-learning workloads.

This role is for a software engineer in the Compiler team for AWS Neuron. As part of this role, you will be responsible for building next generation Neuron compiler which transforms ML models written in ML frameworks (e.g, PyTorch, TensorFlow, and JAX) to be deployed on AWS Inferentia and Trainium based servers in the Amazon cloud. You will be responsible for solving hard compiler optimization problems to achieve optimum performance for variety of ML model families including massive scale large language models like Llama, Deepseek, and beyond as well as stable diffusion, vision transformers and multi-model models. You will be required to understand how these models work inside-out to make informed decisions on how to best coax the compiler to generate optimal implementation instruction. You will leverage your technical communications skill to partner with internal and external customers/stakeholders and will be involved in pre-silicon design, bringing new products/features to market, ultimately, making Neuron compiler highly performant and easy-to-use.

Experience in object-oriented languages like C++/Java is a must, experience with compilers or building ML models using ML frameworks on accelerators (e.g., GPUs) is preferred but not required. Experience with technologies like OpenXLA, StableHLO, MLIR will be added bonus!

Key job responsibilities

You will design, implement, test, deploy and maintain innovative software solutions to transform Neuron compiler’s performance, stability and user-interface. You will work side by side with chip architects, runtime/OS engineers, scientists and ML Apps teams to seamlessly deploy state of the art ML models from our customers on AWS accelerators with optimal cost/performance benefits. You will have opportunity to work with open-source software (e.g., StableHLO, OpenXLA, MLIR) to pioneer optimizing advanced ML workloads on AWS software and hardware. You will also work on building innovative features that will deliver best possible experiences for our customers – developers across the globe.

A day in the life

As you design and code solutions to help our team drive efficiencies in compiler architecture, you’ll create compiler optimization and verification passes, build features surface features and peculiarities of AWS accelerators to developers, implement tools to analyze numerical errors, and resolve the root cause of compiler defects. You’ll also participate in design discussions, code review, and communicate with internal (other Neuron SDK and Amazon wide teams) and external stakeholders (open-source communities). Lastly, work in a startup-like development environment, where you’re always working on the most important stuff.

About the team

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.

BASIC QUALIFICATIONS
  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language
PREFERRED QUALIFICATIONS
  • Master's degree or PhD in Computer Science, or a related technical field.
  • 3+ years of experience writing production grade code in object-oriented languages such as C++/Java.
  • Experience in compiler design for CPU/GPU/Vector engines/ML-accelerators.
  • Experience with OpenSource compiler toolset like LLVM/MLIR.
  • Experience with the following technologies: PyTorch, OpenXLA, StableHLO, JAX, TVM, deep learning models, and algorithms.
  • Experience with modern build systems like Bazel/CMake.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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