Amazon
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 AWS Machine Learning accelerators (Inferentia/Trainium) offer unparalleled ML inference and training performances. They are enabled through a state‑of‑the‑art software stack – the AWS Neuron SDK – which comprises an ML compiler, runtime, and application framework that seamlessly integrates with 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.
Annapurna Labs was a startup company acquired by AWS in 2015 and is now fully integrated. Our organization spans multiple disciplines, including silicon engineering, hardware design and verification, software, and operations. Across the years, we have delivered high‑performance products such as AWS Nitro, ENA, EFA, Graviton, and F1 EC2 instances, as well as storage solutions with scalable NVMe.
Within this ecosystem, the Neuron Compiler team develops a deep learning compiler stack that takes state‑of‑the‑art LLM, Vision, and multimodal models created in frameworks such as TensorFlow, PyTorch, and JAX, and makes them run performantly on our accelerators. The team consists of bright minds in engineering, research, and product communities with an 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 optimization 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 optimizations but also works to crystallize these improvements into the compiler, automating optimizations for broader customer benefit.
This role offers an opportunity to work on products at the intersection of machine‑learning, high‑performance computing, and distributed architectures. You will architect and implement business‑critical features, publish 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 are inventing, experimenting, and learning in a unique culture that values direct customer collaboration to optimize machine learning workloads on AWS ML accelerators.
Explore the product and our history:
Neuron guide:
https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html
AWS Neuron overview:
https://aws.amazon.com/machine-learning/neuron/
AWS Neuron SDK GitHub:
https://github.com/aws/aws-neuron-sdk
Academia article:
https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success
Key job responsibilities
Analyze and optimize 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 optimize their ML models on AWS accelerators, understanding their specific requirements and use cases.
Design and implement compiler optimizations, transforming manual performance improvements into automated compiler passes.
Collaborate across teams to develop innovative optimization 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.
About the team
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed, we encourage candidates to apply.
Why AWS: Amazon Web Services is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating.
Inclusive Team Culture: We embrace our differences and are committed to furthering our culture of inclusion, hosting annual and ongoing learning experiences.
Work/Life Balance: Our team puts a high value on work‑life balance, encouraging flexibility and a healthy balance between personal and professional life.
Mentorship & Career Growth: Our team is dedicated to supporting new members, building an environment that celebrates knowledge sharing and mentorship.
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
3+ 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.
Experience in compiler design for CPU/GPU/Vector engines/ML‑accelerators.
Experience with System Level performance analysis and optimization.
Experience with LLVM and/or MLIR.
Experience with the following technologies: PyTorch, OpenXLA, StableHLO, JAX, TVM, deep learning models, and algorithms.
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.
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The AWS Machine Learning accelerators (Inferentia/Trainium) offer unparalleled ML inference and training performances. They are enabled through a state‑of‑the‑art software stack – the AWS Neuron SDK – which comprises an ML compiler, runtime, and application framework that seamlessly integrates with 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.
Annapurna Labs was a startup company acquired by AWS in 2015 and is now fully integrated. Our organization spans multiple disciplines, including silicon engineering, hardware design and verification, software, and operations. Across the years, we have delivered high‑performance products such as AWS Nitro, ENA, EFA, Graviton, and F1 EC2 instances, as well as storage solutions with scalable NVMe.
Within this ecosystem, the Neuron Compiler team develops a deep learning compiler stack that takes state‑of‑the‑art LLM, Vision, and multimodal models created in frameworks such as TensorFlow, PyTorch, and JAX, and makes them run performantly on our accelerators. The team consists of bright minds in engineering, research, and product communities with an 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 optimization 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 optimizations but also works to crystallize these improvements into the compiler, automating optimizations for broader customer benefit.
This role offers an opportunity to work on products at the intersection of machine‑learning, high‑performance computing, and distributed architectures. You will architect and implement business‑critical features, publish 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 are inventing, experimenting, and learning in a unique culture that values direct customer collaboration to optimize machine learning workloads on AWS ML accelerators.
Explore the product and our history:
Neuron guide:
https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html
AWS Neuron overview:
https://aws.amazon.com/machine-learning/neuron/
AWS Neuron SDK GitHub:
https://github.com/aws/aws-neuron-sdk
Academia article:
https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success
Key job responsibilities
Analyze and optimize 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 optimize their ML models on AWS accelerators, understanding their specific requirements and use cases.
Design and implement compiler optimizations, transforming manual performance improvements into automated compiler passes.
Collaborate across teams to develop innovative optimization 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.
About the team
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed, we encourage candidates to apply.
Why AWS: Amazon Web Services is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating.
Inclusive Team Culture: We embrace our differences and are committed to furthering our culture of inclusion, hosting annual and ongoing learning experiences.
Work/Life Balance: Our team puts a high value on work‑life balance, encouraging flexibility and a healthy balance between personal and professional life.
Mentorship & Career Growth: Our team is dedicated to supporting new members, building an environment that celebrates knowledge sharing and mentorship.
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
3+ 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.
Experience in compiler design for CPU/GPU/Vector engines/ML‑accelerators.
Experience with System Level performance analysis and optimization.
Experience with LLVM and/or MLIR.
Experience with the following technologies: PyTorch, OpenXLA, StableHLO, JAX, TVM, deep learning models, and algorithms.
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.
#J-18808-Ljbffr