Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop machine learning algorithms for high-scale recommendations and collaborate with teams globally.
- Company: Join Prime Video, a leading streaming service transforming how customers enjoy movies and TV shows.
- Benefits: Enjoy opportunities for growth, remote work options, and the chance to make a global impact.
- Why this job: Be part of an innovative team shaping the future of entertainment with cutting-edge technology.
- Qualifications: Master's degree in a quantitative field and experience in programming and machine learning required.
- Other info: This role offers hands-on experience in a dynamic, fast-paced environment.
The predicted salary is between 48000 - 84000 £ per year.
Social network you want to login/join with:
col-narrow-left
Client:
Location:
London, United Kingdom
Job Category:
Other
–
EU work permit required:
Yes
col-narrow-right
Job Reference:
7713c09d4bcd
Job Views:
26
Posted:
24.06.2025
Expiry Date:
08.08.2025
col-wide
Job 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 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 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 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 Insights team is looking for an Applied Scientist for our London office experienced in generative AI and large models. This is a hands-on role with Prime Video wide impact working with development teams across the UK, India, and the US. This greenfield project will deliver features that reduce the operational load for internal Prime Video builders and for this, you will need to develop personalized recommendations for their services.
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.
Successful candidates will have strong technical ability, excellent teamwork and communication skills, and a strong motivation to deliver customer value from their research. Our position offers exceptional opportunities for every candidate to grow their 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.
– Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports.
About the team
Our team owns Prime Video observability features for development teams. We consume PBs of logs daily which feed into multiple observability features focussed on reducing the customer impact time. In 2025, we are expanding our remit to consume data from more sources to provide more holistic observability for our development teams.
BASIC QUALIFICATIONS
– Master\’s degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
– Experience programming in Java, C++, Python or related language
– Experience with neural deep learning methods and machine learning
– Experience in building machine learning models for business application
– Experience in applied research
PREFERRED QUALIFICATIONS
– Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
– Experience with large scale distributed systems such as Hadoop, Spark etc.
– PhD
#J-18808-Ljbffr
Senior Applied Scientist, Insights, Prime Video employer: Amazon Development Centre (London) Limited
Contact Detail:
Amazon Development Centre (London) Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Applied Scientist, Insights, Prime Video
✨Tip Number 1
Familiarise yourself with the latest trends in generative AI and large models. Understanding the current landscape will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the industry, especially those working in machine learning and applied science roles. Attend relevant meetups or webinars to make connections that could lead to referrals.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those involving machine learning algorithms and their business applications. Be ready to explain your thought process and the impact of your work.
✨Tip Number 4
Showcase your teamwork and communication skills by preparing examples of how you've collaborated with cross-functional teams. Highlight any experiences where you successfully communicated complex technical concepts to non-technical audiences.
We think you need these skills to ace Senior Applied Scientist, Insights, Prime Video
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, programming languages like Python or Java, and any applied research you've conducted. Emphasise your ability to work in a team and communicate complex ideas clearly.
Craft a Compelling Cover Letter: In your cover letter, express your passion for shaping the future of entertainment through technology. Mention specific projects or experiences that demonstrate your expertise in generative AI and large models, and how they align with the goals of Prime Video.
Showcase Your Technical Skills: Include specific examples of machine learning algorithms you've developed or worked on, particularly those that relate to high-scale recommendations. Highlight any experience with tools like TensorFlow or Spark, as well as your programming proficiency.
Prepare for Interviews: Be ready to discuss your past projects in detail, especially those involving collaboration with engineering teams. Prepare to explain your thought process in designing experiments and how you communicate results to both technical and non-technical audiences.
How to prepare for a job interview at Amazon Development Centre (London) Limited
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms and programming languages like Python or Java. Bring examples of past projects where you've successfully implemented these skills, especially in high-scale environments.
✨Demonstrate Collaboration
Since the role involves working with teams across different countries, highlight your teamwork and communication skills. Share specific instances where you collaborated with engineers or other scientists to achieve a common goal.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to design and test hypotheses in ambiguous situations. Practice articulating your thought process when approaching complex problems, as this will showcase your analytical skills.
✨Communicate Clearly
You’ll need to present insights to both technical and non-technical audiences. Practice explaining your research and findings in simple terms, ensuring you can convey complex ideas effectively to diverse stakeholders.
