Sr. Software Development Engineer, MLOPs

Amazon.com Inc

Bellevue, WA

JOB DETAILS
SKILLS
Best Practices, Capacity Management, Continuous Deployment/Delivery, Continuous Integration, Cost Control, Data Management, Data Modeling, Data Sets, Distributed Computing, Fleet Management, GPU (Graphics Processing Unit), Industrial Robotics, Large-Scale Systems, Machine Learning, Machine Tool, Machining Operations, Management Strategy, Modeling Languages, Order/Customer Fulfillment, Performance Modeling, Product Demonstration, Public/Media/Press/Analyst Relations, Robotics, Scientific Research, Software Development, Software Engineering, Telemetry, Training/Teaching
LOCATION
Bellevue, WA
POSTED
8 days ago

We are looking for a Senior Software Development Engineer with deep expertise in machine learning operations to join the Data & Intelligence Foundation (DIF) team within Amazon. You will design, build, and operate the ML training infrastructure that enables robot learning at scale - from distributed GPU training pipelines to experiment tracking, data management, and model deployment.

Our team is building the foundational ML platform that powers autonomous robotics across Amazon's fulfillment network. You'll work at the intersection of large-scale distributed systems and cutting-edge ML research, turning novel vision-language-action models into production training workflows.

Key job responsibilities

  • Design and implement scalable ML training infrastructure on Kubernetes (EKS) with GPU scheduling and fault-tolerant distributed training
  • Build and maintain CI/CD pipelines for ML models - from data ingestion through training, evaluation, and deployment
  • Develop tooling for experiment tracking, hyperparameter optimization, and reproducibility
  • Architect data pipelines that handle large-scale robotics datasets (telemetry, sensor recordings, demonstrations)
  • Collaborate with research scientists to operationalize novel ML models into production
  • Establish monitoring, alerting, and observability for training workloads and model performance
  • Drive best practices for GPU fleet management, cost optimization, and capacity planning

A day in the life

You'll spend your mornings reviewing training job health across our GPU cluster, debugging a distributed training run that hit a node failure overnight, and shipping a fix to our checkpoint recovery system. After lunch, you'll pair with a research scientist to optimize their new imitation learning model for multi-node training, then architect a new data pipeline to ingest demonstration recordings from robot workcells. You'll close the day reviewing a PR from a teammate and planning the next iteration of our experiment tracking platform.

About the team

The Data & Intelligence Foundation (DIF) team builds the ML infrastructure platform for Amazon's industrial robotics. We enable scientists to train, evaluate, and deploy models that power autonomous robots in fulfillment centers worldwide. We're a small, high-impact team where every engineer shapes the architecture and directly accelerates robot intelligence. We value pragmatic engineering, deep technical ownership, and close collaboration with research.

About the Company

A

Amazon.com Inc

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
COMPANY SIZE
10,000 employees or more
INDUSTRY
Retail
FOUNDED
1994
WEBSITE
http://Amazon.com/militaryroles