- 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 - 8+ years of leading the definition and development of multi tier web services experience - Experience partnering with product or program management teams - Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations - 3+ Years of Deep Learning/Machine learning experience - 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 Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 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 <a href="https://amazon.jobs/content/en/how-we-hire/accommodations">https://amazon.jobs/content/en/how-we-hire/accommodations</a> 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 $166,400/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 <a href="https://www.aboutamazon.com/workplace/employee-benefits">https://www.aboutamazon.com/workplace/employee-benefits</a>. This position will remain posted until filled. Applicants should apply via our internal or external career site. 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. Includes enabling models using MoE architectures and future newer architectures. 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 Key job responsibilities Our engineers and managers collaborate across diverse teams, projects, and environments to have a firsthand impact on our global customer base. You’ll bring a passion for innovation, data, search, analytics, and distributed systems. You’ll also: Solve challenging technical problems, often ones not solved before, at every layer of the stack. Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security. Build high-quality, highly available, always-on products. Research implementations that deliver the best possible experiences for 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 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. About AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship &amp; Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our US Amazon offices. Our hybrid models allow you the freedom to work from home whenever in-office collaboration isn’t necessary.