Virtual Try-on (VTO) at Amazon Fashion & Fitness is looking for an exceptional Applied Scientist to join us to build our next generation virtual try on experience.
Our goal is to help customers evaluate how products will fit and flatter their unique self before they ship, transforming customers' shopping into a personalized journey of inspiration, discovery, and evaluation.
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 (PBR) 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 2D / 3D Virtual Try-on, Neural Avatars, Parametric Body Models, and Differentiable Rendering / Simulation will be highly advantageous.
Key job responsibilities
- Explore, collect, and process data
- Convert highly ambiguous business problems to science problems, build the-state-of-the-art solutions, and evaluate them through offline and online experimentation.
- Lead science initiatives and work across teams to deliver end to end.
- Design and build automated, scalable pipelines to train and deploy ML models
BASIC QUALIFICATIONS
- 5+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 4+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision, computer graphics, and generative AI.
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