Software Development Engineer II, AWS SageMaker AI Training Job

Description

SageMaker AI Training Job team is looking for a Software Development Engineer!

This is a great opportunity to join the SageMaker Training Job team, which lies at the very core of SageMaker. SageMaker Training is a set of managed services that allow customers to train machine learning models using large datasets on managed infrastructure. As the industry leader, SageMaker training is the fastest, easiest, and most cost-effective platform for data scientists to train their models. Learn more at https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works-training.html.

You will be responsible for building and maintaining mission-critical systems in our best-in-class machine learning platform, and scale those systems to support training jobs that run on hundreds of thousands of machines with less than 0.1% failure rate.

You will constantly experiment with new technologies and ideas in order to innovate on our platform and help ensure SageMaker remains best-in-class.

You will be expected to perform at the highest levels of engineering and operational excellence: building highly resilient and scalable systems, writing clear and effective documents, actively contribute to discussions on technical direction and strategy, and raise the bar on all fronts.

Most importantly, you will get to work with a team of highly talented engineers who have all answered the call above and strive for new heights every day.

Key job responsibilities
As a Software Development Engineer on the SageMaker AI team, you will:
- Design, build, test, and operate services that orchestrate foundation-model data preparation, training, evaluation, and deployment as reliable, contract-validated workflows.
- Own delivery of individual components end-to-end — from design and implementation through deployment, monitoring, and on-call operations.
- Build and extend compute-backend integrations and job launchers — submitting, monitoring, and recovering large-scale training jobs across SageMaker (Training/Processing), and AWS Batch.
- Improve the platform's resiliency and operability for long-running distributed jobs — checkpoint/resume, fault detection and recovery, retries, and observability (metrics, logging, experiment tracking).
- Contribute to the SDK, workflow orchestration, and schema/contract layer that teams use to declare and run jobs, and to the CDK infrastructure that deploys the platform.
- Integrate containerized training and evaluation frameworks (e.g., PyTorch/FSDP, verl, NeMo/Megatron) into the platform's task and recipe model.
- Contribute to design and architecture discussions, write clear technical designs, and uphold engineering best practices (code review, testing, operational readiness).
- Collaborate with ML scientists and internal customers to translate training requirements into reliable, self-service platform capabilities, and help onboard and mentor interns and new engineers as you grow.

Basic Qualifications

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 1+ years of software development engineer or related occupational experience
- 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
- 1+ years of Object Oriented Design experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- Experience programming with at least one software programming language

Preferred Qualifications

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience building complex software systems that have been successfully delivered to customers
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience debugging, profiling, and implementing best software engineering practices in large-scale systems

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.

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 - 143,700.00 - 194,400.00 USD annually