Job Location: Seattle, WA
- 1+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems.
- 2+ years of non-internship professional software development experience
- Programming experience with at least one software programming language.
Amazon Prime Video is changing the way millions of customers enjoy digital content. Prime Video delivers premium content to customers through purchase and rental of movies and TV shows, unlimited on-demand streaming through Amazon Prime subscriptions, add-on channels like Showtime and HBO, and live concerts and sporting events like NFL Thursday Night Football. In total, Prime Video offers nearly 200,000 titles and is available across a wide variety of platforms and continues to invest in the future of video through Amazon Studios and produce original movies and TV shows, many of which have already earned critical acclaim and top awards, including Oscars, Emmys and Golden Globes.
The Worldwide Marketplace Science (WMS) team is the ML and analytics partner to global Marketplace businesses. We act as a force-multiplier for marketplace Prime Video content by leveraging ML models and software systems to supercharge acquisition, engagement, retention, and monetization.
As a Software Engineer, you will work side-by-side with science and engineering teams to build and automate ML models and to build tooling to accelerate model development and monitoring. You will take ownership over software design, documentation, development, engineering. You will play an active role in translating business and functional requirements into concrete deliverables and build quick prototypes or proofs of concept in partnership with other technology leaders within the team. You will help invent new features, and develop and deploy highly scalable ML libraries and frameworks.
Key job responsibilities
- Design and build scalable ML infrastructure that enables training, evaluating and deploying machine learning models over billions of data points.
- Design and develop tools for monitoring the performance of machine learning models at scale.
- Design and develop lineage and artifact tracking infrastructure for training data, ML models and experiments.
- Build reproducible ML Pipelines orchestrating various components for ML models.
- Embrace and champion engineering best practices within your group and beyond.
- Produce clean, high-quality code, tests, and written documentation.
- Possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
- Explore and learn the latest AWS/other technologies to provide new capabilities and increase efficiency.
- Experience in building large-scale machine-learning infrastructure.
- Advanced knowledge of performance, scalability, enterprise system architecture, and engineering best practices.
- Ability to deal well with ambiguous and undefined problems.
- Experience with web-scale data processing using Spark or similar technologies.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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