Amazon
Software Engineer - AI/ML, AWS Neuron Distributed Training
Amazon, Seattle, Washington, us, 98127
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.
AWS Neuron is the complete software stack for the AWS Inferentia (Inf1/Inf2) and Trainium (Trn1), our cloud-scale Machine Learning accelerators. This role is for a machine learning engineer in the Distribute Training team for AWS Neuron, responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive-scale Large Language Models (LLM) such as GPT and Llama, as well as Stable Diffusion, Vision Transformers (ViT) and many more.
The ML Distributed Training team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with Trainium instances. Experience with training these large models using Python is a must. FSDP (Fully-Sharded Data Parallel), Deepspeed and other distributed training libraries are central to this and extending all of this for the Neuron based system is key.
Key job responsibilities
You will help lead the efforts building distributed training support into Pytorch, Tensorflow using XLA and the Neuron compiler and runtime stacks. You will help tune these models to ensure highest performance and maximize the efficiency of them running on the custom AWS Trainium and Inferentia silicon and the Trn1, Inf1/2 servers. Strong software development and Machine Learning knowledge are both critical to this role.
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.
Minimum Requirements
Bachelor's degree in computer science or equivalent3+ years of non-internship professional software development experience2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experienceExperience programming with at least one software programming languageExperience in machine learning, data mining, information retrieval, statistics or natural language processing- Master's degree in computer science or equivalent- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience- Experience in computer architecture- Previous software engineering expertise with Pytorch/Jax/Tensorflow, Distributed libraries and Frameworks, End-to-end Model Training.- Previous experience with training multi-modal models for understanding and generating images/videos/audios
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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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.
AWS Neuron is the complete software stack for the AWS Inferentia (Inf1/Inf2) and Trainium (Trn1), our cloud-scale Machine Learning accelerators. This role is for a machine learning engineer in the Distribute Training team for AWS Neuron, responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive-scale Large Language Models (LLM) such as GPT and Llama, as well as Stable Diffusion, Vision Transformers (ViT) and many more.
The ML Distributed Training team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with Trainium instances. Experience with training these large models using Python is a must. FSDP (Fully-Sharded Data Parallel), Deepspeed and other distributed training libraries are central to this and extending all of this for the Neuron based system is key.
Key job responsibilities
You will help lead the efforts building distributed training support into Pytorch, Tensorflow using XLA and the Neuron compiler and runtime stacks. You will help tune these models to ensure highest performance and maximize the efficiency of them running on the custom AWS Trainium and Inferentia silicon and the Trn1, Inf1/2 servers. Strong software development and Machine Learning knowledge are both critical to this role.
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.
Minimum Requirements
Bachelor's degree in computer science or equivalent3+ years of non-internship professional software development experience2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experienceExperience programming with at least one software programming languageExperience in machine learning, data mining, information retrieval, statistics or natural language processing- Master's degree in computer science or equivalent- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience- Experience in computer architecture- Previous software engineering expertise with Pytorch/Jax/Tensorflow, Distributed libraries and Frameworks, End-to-end Model Training.- Previous experience with training multi-modal models for understanding and generating images/videos/audios
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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