Description Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. We are looking for an applied scientist who will work on the latest research and machine learning to build scalable personalisation solutions. You will be responsible for developing and disseminating customer-facing personalised recommendation models. This is a hands-on role working with a multidisciplinary group of engineers and scientists in the London office, focused on improving the customer experience for Prime Video and the wider Amazon organization. You will lead the design of machine learning models that scale to large quantities of data and serve low-latency recommendations to all customers worldwide. You will embody scientific rigor in designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science and engineering team that embodies the customer obsession principle by developing recommendation systems and raise the profile of Amazon as a global leader in machine learning and personalisation. Successful candidates will have strong technical ability, a focus on customers by applying a customer-first approach, and excellent teamwork and communication skills. The position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. Key job responsibilities - Research, design, and implement recommendation systems that personalise across different customer experience touch points. - Collaborate with engineers to deploy and integrate successful model experiment results into large-scale, complex Amazon production systems with low latency. - Provide machine learning thought leadership to both technical and business leaders, with the ability to think strategically about business, product, and technical challenges. - Define the science roadmap and research agenda that aligns with the organisation's priorities and production constraints. - Work with technical product managers to work backwards from what's important to customers and deliver machine-backed solutions. - Report and share results with the team and wider scientific community by authoring documents that are both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. A day in the life You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and leaders in the Offer Tech organisation. You will be innovating and experimenting in a complex technical and business space - dealing with Amazon scale, different types of video assets (Movies, TV Shows, Live Sports, Short Videos) and balancing various business offerings (Prime, Third party channels), positively impacting millions of customers worldwide using your knowledge research, experience in building ML models to positively impact customers. About the team As a member of the Offer Recommendations team, you will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At then of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. Basic Qualifications - PhD, or a Master's degree and experience in CS, CE, ML or related field research - Experience programming in Java, C++, Python or related language - Experience in building machine learning models for business application - Experience with contextual bandits, off-policy evaluation and learning to rank models - Experience with AWS technologies such as CDK, Redshift, S3, AWS Glue, Sagemaker, Kinesis, FireHose, Lambda, and IAM roles and permissions. - Experience of building machine learning models for business application Preferred Qualifications - Experience using Unix/Linux - Experience in professional software development - Experience working within an Agile environment working with software engineers to launch products for customers. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy\_page) to know more about how we collect, use and transfer the personal data of our candidates. 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/content/en/how-we-hire/accommodations.