Sr Software Engineer - Machine Learning Engineer, AWS Neuron

Full-time
We are looking for a Software Development Engineer to join the AWS Neuron team – the software that empowers the AWS Inferentia-based Inf1 and Trainium-based Trn1 instances. This role is for engineers who take pride in tackling hardest challenges, excel at working in an agile environment, and are excited about accelerating workloads on the Inferentia and Trainium hardware.

You will work with the ML Applications team that develops features using Python and C++ across multiple frameworks like Tensorflow, MXNet and PyTorch. You will interact with a diverse team of AWS solution architects, customer representative, complier and hardware engineers to optimize and deliver cost-effective and performant solutions on the AWS Inferentia and Trainium architecture (for example: [url=https://github.com/aws/aws-neuron-sdk/]https://github.com/aws/aws-neuron-sdk/[/url])


About Us

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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

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.


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. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.



A day in the life
Machine Learning Engineers are specialized software engineers. Amazon Machine Learning Engineers will:
• Design, build, and test ML frameworks and libraries features on behalf of customers.
• Work with product management teams to define product features and roadmaps.
• Investigate and drive new features teams may want to implement.
• Build and maintain continuous integration pipelines for delivery of features.
• Run benchmarks to compare performance and accuracy across different models and platforms.
• Work with other teams such as compiler and runtime teams to improve performance and accuracy of the products.
• Create and maintain documentation for customers.
• Resolve customer issues encountered while using products.

We are open to hiring candidates to work out of one of the following locations:

Cupertino, CA, USA
Apply Now

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We are looking for a Software Development Engineer to join the AWS Neuron team – the software that empowers the AWS Inferentia-based Inf1 and Trainium-based Trn1 instances. This role is for engineers who take pride in tackling hardest challenges, excel at working in an agile environment, and are excited about accelerating workloads on the Inferentia and Trainium hardware.

You will work with the ML Applications team that develops features using Python and C++ across multiple frameworks like Tensorflow, MXNet and PyTorch. You will interact with a diverse team of AWS solution architects, customer representative, complier and hardware engineers to optimize and deliver cost-effective and performant solutions on the AWS Inferentia and Trainium architecture (for example: [url=https://github.com/aws/aws-neuron-sdk/]https://github.com/aws/aws-neuron-sdk/[/url])


About Us

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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

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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.


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A day in the life
Machine Learning Engineers are specialized software engineers. Amazon Machine Learning Engineers will:
• Design, build, and test ML frameworks and libraries features on behalf of customers.
• Work with product management teams to define product features and roadmaps.
• Investigate and drive new features teams may want to implement.
• Build and maintain continuous integration pipelines for delivery of features.
• Run benchmarks to compare performance and accuracy across different models and platforms.
• Work with other teams such as compiler and runtime teams to improve performance and accuracy of the products.
• Create and maintain documentation for customers.
• Resolve customer issues encountered while using products.

We are open to hiring candidates to work out of one of the following locations:

Cupertino, CA, USA
Full-time
APPLY

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About Us

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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

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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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

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About Us

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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

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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.

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