- 2+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience programming with at least one software programming language
- Experience building complex software systems that have been successfully delivered to customers
- Bachelor's degree in computer science or equivalent
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
- Knowledge of large language models and experience in prompt engineering
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.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Do you want to take on one of the most important engineering challenges to shape the future of video streaming? Join us to define the next generation of how and what Amazon customers will be watching!
Prime Video (PV) is a premium streaming service that offers customers the greatest choices in what to watch, and how to watch it. PV's mission is to become the global entertainment destination for customers to enjoy movies, TV shows and live events streamed instantly to all of their devices including TVs, tablets, game consoles and PCs worldwide. We are a young and evolving business within Amazon where creativity and drive can have a lasting impact on the way video is enjoyed worldwide. You will be encouraged to see the big picture, be creative, and positively impact millions of customers. We’re building the future of streaming — yes, it’s challenging, but it’s also a lot of fun.
The Prime Video Dynamic Groupings team is looking for a Software Development Engineer with a strong technical background, experience in building large-scale machine learning models with real-time systems in a production environment, and a passion for GenAI technology and digital entertainment. Together, we will innovate to be the best in class for grouping and presenting video content personalized for every customer that resonates and excites them.
Key job responsibilities
You will work with a team of talented engineers and cross-functional partners including Product and Science to deliver innovations to our global customers to build a long-term relationship with Prime Video by bringing them back to the service, curates and personalizes their storefront to highlight the diversity and depth of the PV catalog.
You will build solutions that leverage the latest technologies including large language models and other machine learning techniques. You will work with (1) high volumes of data (2) use known models or optimized models (3) set up ML training infrastructure and (4) test and validate your changes in production worldwide.
A successful candidate will have strong technical skills, great analytical reasoning ability, excellent communication skills, high creativity, and motivation to achieve results in a fast-paced environment. You should also have industry experience in building scalable systems, working with large data sets and ML models, understanding their limitations and best practices. You feel comfortable adapting to evolving requirements based on learnings. Lastly, it would be ideal if you have a passion for entertainment including movies, TV show and live events.
A day in the life
You will actively participate in the end-to-end software development lifecycle for the platforms and features we own - including requirements gathering, system design and implementation, testing and ongoing support. Our tech stack includes API gateway, Lambdas, S3, DynamoDB, SageMaker, model inference pipelines and complex caching techniques. Our team embraces agile methodologies with a focus on test automation and continuous deployment. Moreover, you will exchange ideas with your Product and Applied Science partner to influence and shape the future of our content personalization strategy.
About the team
The Dynamic Groupings team is part of the Prime Video Personalization and Discovery (PVPD) organization. PVPD's vision is to make Prime Video every customers' trusted friend by responding to their needs, evolving with their moods, and inspiring their next delightful stream in every visit. Our team helps drive this vision by being the expert in grouping and presenting video content to customers that resonates and excites them. We use state-of-the art LLMs and other ML techniques to understand similarities between titles, create personalized naming and groupings of title recommendation to customers that echos their interest and culture (eg. dystopian sci-fi based on a book)
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