- SageMaker is one of the fastest growing AWS services. You will join the founding team in building an end-to-end ML pipeline platform in SageMaker. It represents a unique opportunity to contribute in developing a new pillar for Amazon's ML platform.
- Applying ML in real-life is still in its early stage and ML practitioners face similar challenges as software engineering teams faced a decade ago. Our mission is to solve challenges in ML like what DevOps solved for software development over the past 10 years. This is a new area in ML with lots of evolvement in concepts, methodology, and solutions.
- We have a deep mix of senior talent presenting itself in Principals and Distinguished Engineers that lead to an extensive level of learning and coaching. This is a great opportunity if you are looking to get into the AI/ML space and want to get hands-on experience building ML platform services at scale.
- Our services are built on native AWS. We embrace modern technologies and server-less/micro-service based architectures, which maximize engineering efficiency and operational excellence.
We own AWS SageMaker (https://w.amazon.com/index.php/AWS/AmazonAI/Platform/IronMan) to empower the world to do more and better Machine Learning.
This is recent launch from team made GA in Q2 2026 (https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-heterogeneous.html)
We are looking for internal candidates with prior experience building large scale systems, who are excited about getting into the ML domain.
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience with CUDA kernels or ML/low-level kernels
- Experience with LLM inference and serving optimization, including kernel tuning (CUDA), latency and throughput tuning, profiling and benchmarking, and model execution techniques such as disaggregated serving and KV caching.
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.
Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue – 168,100.00 - 227,400.00 USD annually
