Sr. Software Engineer- AI/ML, AWS Neuron Apps

Amazon; Seattle (WA); On-site; USD 151,300 - 261,500; Full time

Benefits offered by this job

Flexible working hours

Mentorship and career growth opportunities

Comprehensive benefits package

Job summary

A global technology company in Seattle seeks a Senior Software Engineer for the Machine Learning Applications team. This role involves developing and optimizing distributed inference solutions for large ML models on AWS infrastructure. Candidates should have strong programming skills in C++ and Python, along with substantial experience in machine learning. This position offers competitive compensation and promotes a balanced work-life environment.

Qualifications

• 5+ years of programming using a modern programming language.
• 5+ years of leading design or architecture experience.
• Fundamentals of Machine learning and deep learning models.

Responsibilities

• Lead efforts building distributed inference support into PyTorch and TensorFlow.
• Tune models for highest performance on AWS Trainium and Inferentia.
• Collaborate with chip architects and engineers.

Skills

C++ programming

Python programming

Machine learning knowledge

Object-oriented design

Distributed systems

Education

Bachelor's degree in computer science or equivalent

Job description

Overview

AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This role is for a senior software engineer in the Machine Learning Applications (ML Apps) team for AWS Neuron. This role is responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale large language models like GPT2, GPT3 and beyond, as well as stable diffusion, Vision Transformers and many more.

The ML Apps team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with Trn1. Experience training these large models using Python is a must. FSDP, 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

This role will help lead the efforts building distributed inference support into PyTorch, TensorFlow using XLA and the Neuron compiler and runtime stacks. This role will help tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and the Trn1, Inf1 servers. Strong software development using C++/Python and ML knowledge are both critical to this role.

A day in the life

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. 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.

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.

Qualifications

Basic Qualifications

• 5+ years of programming using a modern programming language such as Java, C++, or C#, including object-oriented design experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Fundamentals of Machine learning and deep learning models, their architecture, training and inference lifecycles along with work experience on some optimizations for improving the model execution

Preferred Qualifications

• 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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/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. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.