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. 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.
Our vision is to ensure customers experience the highest quality video as the service scales to content from any source, available on any device, anywhere. We develop industry-leading mechanisms that allow customers to detect video defects automatically and instantly at any point in the video pipeline, from content origin to end users' devices. We use the expertise we develop to advance the state-of-the-art in objective measures that can detect defects and predict our customers' perceptions of image and audio quality.
The solutions we're building are demanding. Collaborating with teams across Amazon and world-leading universities, we create novel algorithms to assess the presence of defects and overall video quality. This requires the use of the latest technologies across foundational models, transformer-based architectures, masked autoencoders, image processing, image analysis, computer vision, and machine learning. We need to optimise those algorithms to run accurately, efficiently, and quickly so that reliable results are available as close to real-time as possible. The scope of our charter means we're also utilising techniques such as contextual understanding and correction, to ensure the highest levels of video quality for our customers.
The range of problems we have to solve in our space, and the enormous potential to positively impact Prime Video's ability to scale, provides a breadth of opportunities for engineers to grow and develop their skills.
Please Note: This is a 12-month Fixed-Term Contract
Key job responsibilities
Our team develops detectors consisting of deep computer vision and Machine Learning (ML) techniques, requiring team members to conduct research and methods that can identify defects with high accuracy and low friction, optimising to achieve both low latency and cost to operate for customers at scale. This requires depth of science application across all aspects of the ML lifecycle including model training, optimisation, experimentation, and maintenance. Lead engineers are also expected to have a strong understanding of statistics and math, combined with core SDE computer science skills that enable them to dive deep into algorithmic performance, e.g., data structures.
About the team
The team is based in Amazon's engineering centre in London and consists of engineers with a variety of backgrounds, from seasoned Amazonian to newly hired; a mix of applied scientists, machine learning engineers, AWS experts, and generalists, but all of us are learning and growing. We work closely with other Prime Video engineering teams, including teams based on the US west coast and India as well as in London.
Why us? We're a new team with a new charter doing cool stuff with the latest technologies. We trial and error with the boldest innovative ideas. We're building systems at Amazon scale that many others will depend on and the nature of what we're doing means we get to collaborate and work with experts from all across Prime Video.
BASIC QUALIFICATIONS
- Experience contributing to the architecture and design (architecture, design patterns, reliability, and scaling) of new and current systems
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- Experience in professional, non-internship software development
- Master's degree in Machine Learning, Applied Mathematics, Operations Research, or a related field, or equivalent work experience
PREFERRED QUALIFICATIONS
- Bachelor's degree in computer science or equivalent
- Experience with the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience with developing and deploying Machine Learning Operations (MLOps) at scale
- Experience with large scale foundational models and transformer-based architecture (GenAI)
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