Are you excited about building software that empowers scientists to develop new products? As a Software Development Engineer on our team, you will design and deliver systems at the intersection of machine learning and the life sciences. We are scaling our model and method execution infrastructure so scientists can generate, analyze, and deliver new products and insights to researchers and internal teams across Amazon. Today the platform processes thousands of ML inference jobs weekly, and we need a collaborative, curious engineer to help us meet rapidly growing demand. You will work alongside scientists, engineers, and product managers in a startup-like environment where your contributions directly shape products that reach customers and accelerate scientific discovery.
Key job responsibilities
- Design and build scalable ML inference pipelines in collaboration with scientists and engineers, ensuring reliable model execution as data volumes grow.
- Architect and improve the metadata systems that track workflows and their outputs, weighing performance, maintainability, and extensibility trade-offs.
- Evaluate and integrate generative AI tools where they can accelerate development or improve code quality, applying responsible AI practices throughout.
- Contribute to every phase of the software development lifecycle, from requirements gathering and design through implementation, testing, deployment, and operations.
- Conduct thorough code reviews, mentor teammates, and document your software so the broader team can maintain and extend it confidently.
A day in the life
You might start the morning in standup, sharing progress on the inference pipeline you are optimizing. After that, you join a design review where you and your teammates debate the right data model for a new workflow. In the afternoon, you pair with a scientist to prototype a feature, then wrap up by reviewing a teammate's pull request and leaving constructive feedback. Throughout, you balance hands-on coding with cross-team coordination to keep projects moving forward.
About the team
Our team builds the ML execution platform that life-sciences researchers rely on to turn complex scientific models into products customers use every day. We are investing in scaling this platform to handle rapidly growing data, and this is a great moment to join and shape that trajectory.
We are dedicated to supporting every team member's growth. Senior engineers provide one-on-one mentoring and thoughtful code reviews, and we assign projects with an eye toward helping each person become a more well-rounded engineer. We value flexibility, knowledge sharing, and an inclusive environment where every voice is heard.
