Senior Applied Scientist, Prime Video - Compression Efficiency Research Team

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports - including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.

Are you interested in shaping the future of entertainment? Prime Video"s technology teams are creating best-in-class digital video experience.

As a Prime Video technologist, you'll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You'll get to work on projects that are fast-paced, challenging, and varied. You'll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.

We'll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!

This position involves research into and development of advanced DL models for video assets in order to improve their visual quality to be appealing to our customers (e.g. restoration from various defects, improving resolution, restoring truer colors, SDR->HDR up-conversion, better dithering/noising techniques to withstand compression artifacts, etc.). You will also develop next-generation methods for content-adaptive video encoding. You will work closely with subject matter experts (Research Scientists) with depth in the video encoding/quality/processing areas to maximize the video quality that Prime Video customers experience under a given network condition.

Your work would directly influence the customer experience making Prime Video the destination for consuming content at the highest quality.

Key job responsibilities

The work would involve working with creation of ground-truth datasets, creating new video diffusion model architectures and training methodologies that ensure the best temporal consistency, preservation of creative intent, and perceptual quality. You will also work on optimization and deployment of such models in production workflow and will define/measure suitable at-scale success criteria.

Aspects of work can involve scene understanding at a semantic level using latest techniques. You would develop innovative solutions that achieve the best balance between speed vs performance, file invention disclosures, and publish these novel approaches in tier-1 conferences. You would collaborate with research scientists with domain depth in video encoding/compression. You would conduct subjective ratings tests to generate ground truth data for your models, when required. You would also contribute to development of new video quality models that correlate highly with subjective ratings and help quantify the improvements brought about by your work. You would define and refine team processes around ML/DL model development, deployment, and guardrail definition.

A day in the life

You will work with Video Research Scientists who will bring domain expertise to jointly define the specific problem and technical approach. You may collaborate with academia through sponsored research programs on complex problems of long-term importance in your area of work. You will interface with ML engineers to convert your output into production workflows. You will help develop new AI workflows that are more efficient from a compute perspective. You will work with product managers to develop product roadmap that align with business goals. You will help hire new talent and will help develop talent through knowledge sharing and mentorship.