Jobs for People with MS: National MS Society

Description

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. As the SDM of Software Development for the Machine Learning Distributed Training team, you will be responsible for leading a strong team of engineers and managers to help design and deploy these new products. A successful candidate will have an established background in developing Machine Learning products with direct customer-facing experience, a strong technical ability and a motivation to achieve results. Experience in Machine Learning and software development is also a must.

Responsible for the full development life cycle of our integrations and extensions for inference and training support in Pytorch, XLA, JAX as well as distributed training libraries like FSDP, DDP and others.

Characterization, enablement and development of existing and future massive-scale ML models like GPT3 as well as BERT, ViT, LLama, Stable Diffusion and more

Lead the way to ensure support for key ML functionality in a combined chip / software platform

Ensure the right thing is being built and delivered to customers

A day in the life

You will work with the executive leadership and other senior management and technical leaders to define product directions and deliver them to customers. We build massive-scale distributed training and inference solutions. This organization builds the full stack of software, servers and chips to accelerate at the highest scale.

About the team

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 16 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. 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.

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

Cupertino, CA, USA | Seattle, WA, USA

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

• 2 years experience leading teams that in Machine Learning development including building and training large models, working with Pytroch and/or Jax/Tensorflow using large distributed fleets of GPU or other accelerated systems.

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 $148,000/year in our lowest geographic market up to $287,700/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. Applicants should apply via our internal or external career site.