Interested in Machine Learning and AI? Our team's mission is to make machine learning easy, stronger, and universal in the world of Natural Language and Speech. We continuously work on adding new services to our portfolio, which address real world problems through research and innovation. We build state-of-the-art services using the latest deep learning techniques and highly scalable distributed systems engineering.

This role will be part of the Amazon Transcribe team. This team is considered strategic and has visibility with AWS leadership at the highest levels. The role offers a chance to build and scale new and existing AI services and features from the ground up, learn the state of the art in machine learning (ML) technology, and work closely with an exceptional group of product, engineering, and science leaders. ML background is preferred but not required.

Key job responsibilities
As a SDE, you will be responsible for designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions for our world-wide customer base. In this, you will collaborate closely with a team of ML scientists to influence our overall strategy and define the team’s road map. You will also drive the system architecture, spearhead best practices that enable a quality product, and help coach and develop junior engineers. A successful candidate will have an established background in engineering large scale software systems, a strong technical ability, great communication skills, and a motivation to achieve results in a fast paced environment.

About the team
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Hybrid Work
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our US Amazon offices. Our hybrid models allow you the freedom to work from home whenever in-office collaboration isn’t necessary.

We are open to hiring candidates to work out of one of the following locations:

Seattle, WA, USA