At a Glance
- Tasks: Design and develop AI systems for automated incident triage and root cause analysis.
- Company: Join Amazon Prime Video, a leader in the entertainment streaming industry.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Shape the future of entertainment with cutting-edge technology and make a global impact.
- Qualifications: Experience in programming and machine learning; advanced degree preferred.
The predicted salary is between 60000 - 80000 £ 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. 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.
The Observability and Triage team is 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. This greenfield project will deliver features that reduce the operational load for internal Prime Video builders and for this, you will develop AI‑driven solutions that automatically detect anomalies, identify root causes, recommend resolution paths and take action for operational incidents. We consume petabytes of data daily across multiple metric, log and data‑based events and you would be experimenting on how to shape the future through this data.
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.
Key job responsibilities- Design and develop machine learning and generative AI systems for automated incident triage, root cause analysis, and resolution recommendation at scale
- Rapidly prototype and evaluate hypotheses in a high‑ambiguity environment, leveraging both quantitative experimentation and domain expertise in operational systems
- Build evaluation frameworks (including LLM‑as‑a‑Judge approaches) to measure model accuracy across triage accuracy and root cause prediction
- Collaborate with software engineering teams to integrate ML models into production observability systems serving hundreds of development teams
- Communicate results and insights to both technical and non‑technical audiences, including through publications, presentations, and written reports
A day in the life: On a typical day, you analyse patterns across thousands of operational incidents to improve an automated triage model, then design an experiment to test whether a new Generative‑AI based approach better identifies root causes for complex multi‑service incidents. Your internal customers are Prime Video development teams who rely on your solutions to reduce the time and effort spent responding to operational events. You will collaborate closely with software engineers, and operational stakeholders across the world to ensure your research translates into production systems that measurably remove customer impact.
About The Team: Our team builds AI‑powered observability and triage solutions for Prime Video development teams, consuming petabytes of data daily to automatically detect, diagnose, and recommend resolutions for operational incidents.
Basic Qualifications- 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
- PhD, or Master's degree in CS, CE, ML or equivalent relevant work experience
- 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.
Applied Scientist, Observability and Triage, Prime Video employer: Amazon Science
At Prime Video, we are committed to fostering a dynamic and inclusive work culture that empowers our employees to innovate and excel. Located in the vibrant city of London, our team offers unparalleled opportunities for professional growth, collaboration across global teams, and the chance to make a significant impact in the entertainment industry through cutting-edge AI technology. Join us to be part of a forward-thinking environment where your contributions directly enhance the viewing experience for millions worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist, Observability and Triage, Prime Video
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We think you need these skills to ace Applied Scientist, Observability and Triage, Prime Video
Some tips for your application 🫡
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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!
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✨Brush Up on Your Statistics
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