Software Development Manager, SageMaker Training

AI in this role

Lead a software development team building distributed systems and infrastructure for fine-tuning and post-training foundation models.

sagemakerpythondistributed-systems

fine-tuningsoftware-development-managementmachine-learningreinforcement-learningmodel-customization

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 Software Development Manager to lead the team that owns those 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. Your team turns 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 the manager you own the team and its charter. You will hire and grow engineers, set technical direction with your senior engineers and product managers, and decide what the team does and does not build. You own the roadmap and defend its tradeoffs with leadership. You own the service in production, including on-call health, operational metrics, and the customer requests that come with a service in the critical path of customer training workloads.

Key job responsibilities
-Lead a team of highly skilled and driven individuals towards achieving critical business goals.

-Grow talent in the team, coach team members on growth areas and create a promotion paths for strong performers.

-Communicate clearly with our customers and collaborators to reduce ambiguity and mitigate risk.

-Enforce professional software engineering guidelines and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.

-Manage and communicate project deliverables, timelines, and progress.

-Build GenAI based distributed, multi-tenet systems with clear state-full/state-less boundaries.

A day in the life
Technical Leadership:

* Lead the design and development of Model customization capabilities on SageMaker Training.
* Own the technical vision for model customization infrastructure.
* Drive architectural decisions for scalable, resilient systems supporting foundation models

Team & People Management:

* Build, mentor, and grow a world-class team of software engineers and manage their career
* Hire top engineering talent and develop team members' careers
* Foster a culture of innovation, operational excellence, and customer obsession

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.

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
- 8+ years of leading the definition and development of multi tier web services experience
- 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
- Experience partnering with product or program management teams
- Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers

Preferred qualifications

- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy

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 - 184,900.00 - 250,200.00 USD annually

How we rate this

Software Development Manager, SageMaker Training at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Fine TuningSoftware Development ManagementMachine LearningReinforcement LearningModel CustomizationSagemakerPythonDistributed Systems

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where software development management was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where reinforcement learning was part of your work. What did you do?
Tell me about a project where model customization was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Fine Tuning, Software Development Management, Machine Learning, Reinforcement Learning, and Model Customization. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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