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Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

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Amazon Senior Applied Scientist, Amazon Fashion & Fitness in New York, New York

Description

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

We are open to hiring candidates to work out of one of the following locations:

New York, NY, USA | Seattle, WA, USA | Sunnyvale, CA, USA

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.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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