Sr. ML Performance Engineer, AWS Neuron, Annapurna Labs

Amazon; Toronto; On-site; CAD 100,000 - 130,000; Full time

Job summary

A leading cloud service provider in Toronto is seeking experienced performance engineers for their machine learning team. In this role, you will analyze and optimize machine learning models, design compiler optimizations, and collaborate across teams to enhance SDK performance. The ideal candidate has extensive software development experience and a background in distributed systems and machine learning. This position promises a dynamic environment focused on innovation and customer success.

Benefits

Flexible working hours

Inclusive culture

Mentorship opportunities

Work-life balance

Qualifications

• 5+ years of non-internship professional software development experience.
• 5+ years of programming with at least one software programming language.
• 5+ years of leading design or architecture of new and existing systems experience.
• Experience as a mentor or tech lead.

Responsibilities

• Analyze and optimise system-level performance of machine learning models.
• Conduct detailed performance analysis and profiling of ML workloads.
• Work directly with customers to enable and optimise their ML models.
• Design and implement compiler optimisations.
• Collaborate across teams to enhance AWS Neuron SDK’s performance.

Skills

Performance analysis

Machine learning

Distributed systems

Software development

Compiler design

Education

Bachelor's degree in computer science or equivalent

Job description

Description

The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon’s custom machine learning accelerators, Inferentia and Trainium.

The Product: The AWS Machine Learning accelerators (Inferentia/Trainium) offer unparalleled ML inference and training performances. They are enabled through state‑of‑the‑art software stack – the AWS Neuron Software Development Kit (SDK). This SDK comprises an ML compiler, runtime, and application framework, which seamlessly integrate into popular ML frameworks like PyTorch. AWS Neuron, running on Inferentia and Trainium, is trusted and used by leading customers such as Snap, Autodesk, and Amazon Alexa.

The Team: Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and scalable NVMe storage are some of the products we have delivered over the last few years.

Within this ecosystem, the Neuron Compiler team is developing a deep learning compiler stack that takes state‑of‑the‑art LLM, Vision, and multi‑modal models created in frameworks such as TensorFlow, PyTorch, and JAX, and makes them run performantly on our accelerators. The team is comprised of some of the brightest minds in the engineering, research, and product communities, focused on the ambitious goal of creating a toolchain that will provide a quantum leap in performance.

The Neuron team is hiring systems and compiler engineers to solve our customers’ toughest problems. Specifically, the performance team in Toronto is focused on analysis and optimisation of system‑level performance of machine learning models on AWS ML accelerators. The team conducts in‑depth profiling and works across multiple layers of the technology stack – from frameworks and compilers to runtime and collectives – to meet and exceed customer requirements while maintaining a competitive edge in the market. As part of the Neuron Compiler organization, the team not only identifies and implements performance optimisations but also works to crystallise these improvements into the compiler, automating optimisations for broader customer benefit.

This is an opportunity to work on cutting‑edge products at the intersection of machine‑learning, high‑performance computing, and distributed architectures. You will architect and implement business‑critical features, publish cutting‑edge research, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We’re inventing. We’re experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimisation expertise to ensure their machine‑learning workloads achieve optimal performance on AWS ML accelerators.

Explore the product and our history!

https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html

https://aws.amazon.com/machine-learning/neuron/

https://github.com/aws/aws-neuron-sdk

https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success

Key job responsibilities

Our performance engineers collaborate across compiler, runtime, and framework teams to optimise machine learning workloads for our global customer base. Working at the intersection of machine learning, high‑performance computing, and distributed systems, you’ll bring a passion for performance analysis, distributed systems, and machine learning.

• Analyze and optimise system‑level performance of machine learning models across the entire technology stack, from frameworks to runtime
• Conduct detailed performance analysis and profiling of ML workloads, identifying and resolving bottlenecks in large‑scale ML systems
• Work directly with customers to enable and optimise their ML models on AWS accelerators, understanding their specific requirements and use cases
• Design and implement compiler optimisations, transforming manual performance improvements into automated compiler passes
• Collaborate across teams to develop innovative optimisation techniques that enhance AWS Neuron SDK’s performance capabilities
• Work in a startup‑like development environment, where you’re always working on the most important stuff

A day in the life

As you design and code solutions to help our team drive efficiencies in software architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:

• Build high‑impact solutions to deliver to our large customer base
• Participate in design discussions, code review, and communicate with internal and external stakeholders
• Work cross‑functionally to help drive business decisions with your technical input
• Work in a startup‑like development environment, where you’re always working on the most important stuff

About the team

• #1. Diverse Experiences – AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
• #2. Why AWS – Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating – that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
• #3. Inclusive Team Culture – Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee‑led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
• #4. Work/Life Balance – Our team puts a high value on work‑life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life‑long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
• #5. Mentorship & Career Growth – 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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better‑rounded professional and enable them to take on more complex tasks in the future.

Basic Qualifications

• 5+ years of non‑internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team

Preferred Qualifications

• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.