Applied Scientist II, RBS Tech

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects  platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post‑buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations.

As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state‑of‑the‑art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi‑modal understanding (text and images), task automation through multi‑modal LLM agents, supervised and unsupervised techniques, multi‑task learning, multi‑label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results.

• Design and deploy scalable GenAI, NLP and Computer Vision solutions that impact content visible to millions of customers and solve key customer experience issues.
• Develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems.
• Define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time.
• Partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation.
• Coach and mentor teammates, contributing to their technical knowledge and engineering practices.
• Guide the team to file for patents and/or publish research work where opportunities arise.
• Drive resolution of organization‑level problems related to selling partners and end customers, impacting large product strategy and new business opportunities.

• PhD or Master’s degree.
• 1 year of relevant applied research experience with a PhD or 3+ years of applied research experience with a Master’s degree in Electrical Engineering, Computer Science, Computer Engineering, Mathematics, or a related field with specialization in Machine Learning, NLP, Computer Vision, Deep Learning, or GenAI related fields.
• Expert in either Computer Vision or NLP with good understanding of the other.
• Excellent communication skills.

• Post Graduate degree (MS or PhD) in Electrical Engineering, Computer Science, Mathematics, or Physics with specialization in ML, NLP, or Computer Vision.
• Strong verbal/written communication skills and ability to effectively collaborate with research and technical teams.
• Scientific thinking and a track record of thought leadership and contributions that have advanced the field.
• Solid understanding of machine learning, deep learning algorithms, and computational complexity.
• Strong CS fundamentals in data structures, problem solving, algorithm design, and complexity analysis.

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