Applied Scientist, GenAI Evaluation Media

Description

We are seeking an Applied Scientist to join our Generate AI Visual Media - Core Experiences Science team. This organization drives significant business value by revolutionizing how customers interact with product imagery and videos across Amazon. Working at the intersection of Computer Vision and Generative AI, you will help customers make confident purchase decisions through optimized visual content. Our goal is to transform shopping into a personalized journey of inspiration, discovery, and evaluation by helping customers evaluate how products will fit and flatter their unique self before they ship.

In this role, you will be responsible for building scalable computer vision and machine learning (CVML) models, and automating their application and expansion to power customer-facing features.

We are seeking domain expertise specifically in 3D Generative AI and Inverse Rendering. Relevant topics include Neural Fields, Implicit 3D Representations, NeRFs, Differentiable Rendering/Simulation, and Physically Based Rendering (P ) Materials. We expect strong expertise at the intersection of Computer Graphics, Computer Vision, and Deep Learning. An inclination towards Generative AI, such as GANs, VQ-VAE/GAN, and Diffusion Models, is essential. Additionally, experience in application-specific domains such as Neural Avatars, Parametric Body Models, and Differentiable Rendering/Simulation will be highly advantageous.

Key job responsibilities

- Explore, collect, and process data

- Frame and transform ambiguous business challenges into science hypotheses. Design and implement offline and online experiments to evaluate them

- Develop prototypes to test new concepts/proposals for models and algorithms

- Design and build automated, scalable pipelines to train and deploy ML models

Basic Qualifications

- PhD, or Master's degree and 5+ years of CS, CE, ML or related field experience

- 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

Preferred Qualifications

- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms

- Experience in patents or publications at top-tier peer-reviewed conferences or journals

- Experience with popular deep learning frameworks such as Tensor Flow and PyTorch.

- Experience with popular deep learning frameworks such as Tensor Flow and PyTorch.

- Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.

- Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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  (Use the "Apply for this Job" box below).  for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.

Learn more about our benefits at   .

USA, WA, Seattle -  -  USD annually