Sr Software Dev Engineer, SageMaker Training

Interested in building the distributed systems that let customers customize foundation models at scale The SageMaker Training and Model Customization team builds the services customers use to fine-tune and post-train models against their own accuracy reliability and cost targets. We are looking for a Sr Software Development Engineer to build these capabilities.

Model customization is the fastest-moving layer of the machine learning stack. Post-training has gone from supervised fine-tuning to reinforcement learning against verifiable rewards and from single-turn tasks to agentic training where a model learns by acting in an environment over long trajectories. Each shift changes the shape of the workload: reinforcement learning puts an inference engine inside the training loop and agentic training adds environments and tool calls that move the bottleneck from run to run. You turn each new technique into a capability customers can use without rebuilding the platform every time the research moves. Underneath it stays a hard distributed systems problem across large accelerator fleets where a single node failure can halt progression.

As a Senior SDE you own your teams architectural direction including influencing decisions in systems you depend on but dont control. You lead the teams software development alongside peers on related teams and you are responsible for the quality of what it ships. You take on problems where the customer case is defined but the technology strategy is not balancing speed of delivery against the foundation for the future and advocating for the right solution. You are a key influencer in the teams strategy and goals you drive adoption of engineering best practices and you coach and mentor other engineers.

Key job responsibilities
- Design develop and operate the distributed services that run large-scale training and reinforcement learning workloads
- Build the scheduling capacity and fleet-health systems that place customer jobs onto large GPU clusters and keep them running through hardware failure
- Build the infrastructure that hosts and scales the engines including multi-tenant GPU sharing across customers
- Partner with Science Product and partner service teams to translate evolving model and customer requirements into scalable technical solutions
- Maintain a high operational excellence bar for services in the critical path of customer training workloads

About the team
We build the managed services customers use to customize foundation models. A customer brings a task a dataset and a definition of what a good answer is worth and our services run the post-training loop on their behalf. We own that entire path from the customer-facing API down to the training-session infrastructure.

- 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
- Bachelors degree in computer science or equivalent

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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 WA BELLEVUE - 168100.00 - 227400.00 USD annually