Amazon
Software Development Manager - ML Compiler, Annapurna Labs Neuron
Amazon, Cupertino, California, United States, 95014
Software Development Manager - ML Compiler, Annapurna Labs Neuron
The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium delivers the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and JAX. AWS Neuron along with the Inferentia/Trainium chips are used at scale with customers and partners both internal and external to Amazon.
The Team: The Amazon Annapurna Labs team is responsible for building innovation in silicon and software for AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. With such breadth of talent, there's opportunity to learn all of the time. 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. When you couple that with the ability to work on so many different products and services, it's a very unique learning culture.
AWS Utility Computing (UC) provides product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Additionally, this role may involve exposure to and experience with Amazon's growing suite of generative AI services and other cutting-edge cloud computing offerings across the AWS portfolio.
Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
Key job responsibilities
You: We are seeking a talented SW Engineering Manager with strong leadership/mentoring skills to join our Deep Learning Compiler Team. As a Manager III you will be building and leading a team of talented compiler engineers developing graph level optimizations to map SOTA deep learning models efficiently to our accelerator capabilities. You’ll leverage your technical skills to collaborate with ML applications teams and applied scientists developing the models to accelerate research ideas and techniques to bring them to production to faster serve our customers to their performance goals. You will partner with Pytorch, OpenXLA and other open source communities to leverage the work in both directions for the benefit of the machine learning community.
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.
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.
BASIC QUALIFICATIONS
- 3+ years of engineering team management experience - 7+ years of working directly within engineering teams experience - 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience - Experience partnering with product or program management teams
PREFERRED QUALIFICATIONS
- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy - Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers - M.S. or Ph.D. in Computer Science or related technical field - Experience with XLA, TVM, MLIR, LLVM, deep learning models and algorithms, and deep learning framework design. - Interactions with open-source communities, in either a leadership or code contributor role
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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The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium delivers the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and JAX. AWS Neuron along with the Inferentia/Trainium chips are used at scale with customers and partners both internal and external to Amazon.
The Team: The Amazon Annapurna Labs team is responsible for building innovation in silicon and software for AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. With such breadth of talent, there's opportunity to learn all of the time. 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. When you couple that with the ability to work on so many different products and services, it's a very unique learning culture.
AWS Utility Computing (UC) provides product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Additionally, this role may involve exposure to and experience with Amazon's growing suite of generative AI services and other cutting-edge cloud computing offerings across the AWS portfolio.
Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
Key job responsibilities
You: We are seeking a talented SW Engineering Manager with strong leadership/mentoring skills to join our Deep Learning Compiler Team. As a Manager III you will be building and leading a team of talented compiler engineers developing graph level optimizations to map SOTA deep learning models efficiently to our accelerator capabilities. You’ll leverage your technical skills to collaborate with ML applications teams and applied scientists developing the models to accelerate research ideas and techniques to bring them to production to faster serve our customers to their performance goals. You will partner with Pytorch, OpenXLA and other open source communities to leverage the work in both directions for the benefit of the machine learning community.
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.
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.
BASIC QUALIFICATIONS
- 3+ years of engineering team management experience - 7+ years of working directly within engineering teams experience - 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience - Experience partnering with product or program management teams
PREFERRED QUALIFICATIONS
- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy - Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers - M.S. or Ph.D. in Computer Science or related technical field - Experience with XLA, TVM, MLIR, LLVM, deep learning models and algorithms, and deep learning framework design. - Interactions with open-source communities, in either a leadership or code contributor role
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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