At a Glance
- Tasks: Develop machine learning algorithms and collaborate with teams to enhance Prime Video's observability.
- Company: Join Amazon's Prime Video team, shaping the future of entertainment globally.
- Benefits: Competitive salary, diverse work culture, and opportunities for personal and professional growth.
- Other info: Dynamic environment with a focus on innovation and customer value.
- Why this job: Make a global impact in entertainment while working with cutting-edge AI technologies.
- Qualifications: PhD or Master's in relevant fields, programming skills, and experience in machine learning.
The predicted salary is between 63000 - 77000 £ per year.
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 including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at any time 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 200 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.
The PV observability team's mission is to deliver efficient, zero-touch observability solutions that combine log management, tracing, and AI-powered analytics, enabling teams to detect, diagnose, and resolve Prime Video issues at unprecedented speed.
We are looking for an Applied Scientist for our London office experienced in generative AI and large models. This is a wide impact role working with development teams across the UK, India, and the US. You will develop and deploy customized models for PV builders' needs at scale, and explore emerging techniques that help us make better decisions faster for agentic solutions. This is a hands-on role working with a high performing and high visibility multidisciplinary group of engineers and scientists in the London office, focused on improving the PV builders experience for the Prime Video organization.
You will have strong technical ability, excellent teamwork and communication skills, and a strong motivation to deliver customer value from your research. Our position offers opportunities to grow your technical and non-technical skills and make a global impact immediately.
Key job responsibilities:- Develop machine learning algorithms for high-scale recommendations problems
- Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement
- Collaborate with software engineers to integrate successful experimental results into Prime Video wide processes
- 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
You will lead the design of machine learning models that scale to very large quantities of data across multiple dimensions. You will embody scientific rigor, designing and executing experiments to demonstrate the technical effectiveness and business value of your methods. You will work alongside other scientists and engineering teams to deliver your research into production systems.
About The Team:Our team owns Prime Video observability features for development teams. We consume PBs of data daily which feed into multiple observability features focused on reducing the customer impact time.
Basic Qualifications:- PhD, or a Master's degree and experience in CS, CE, ML or related field research
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience in building machine learning models for business application
- Experience using Unix/Linux
- Experience in professional software development
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.
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 for more information.
Applied Scientist, Observability, Prime Video in London employer: Amazon Science
Amazon Science in Edinburgh is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. Employees benefit from opportunities for professional growth and development, while contributing to impactful projects that enhance recruitment technologies. With a focus on cutting-edge AI solutions, this role allows you to play a pivotal part in shaping the future of hiring at one of the world's leading companies.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist, Observability, Prime Video in London
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We think you need these skills to ace Applied Scientist, Observability, Prime Video in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Amazon Science, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Amazon Science. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Amazon Science
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Amazon Science!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
