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 at scale. Our 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).
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 entity extraction and slot tagging for Catalog completeness and consistency, 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.
Key job responsibilities As a Manager, Research Analysis, you will lead a team of Research Analysts (RA), and define the AI strategy for AI/ML and GenAI systems across the organization. You will lead complex initiatives, establish technical standards, and influence executive-level decisions through innovation and deep research.
- Architect and own large-scale AI/ML systems, including distributed LLM deployments, fine-tuning infrastructure, and causal modeling
- You will partner with business, science and engineering teams to identify and solve large and significantly complex problems that require scientific innovation.
- Conduct thorough ML experimentation and make ML model and architecture design choices in the areas of developing prompt abstraction layers, auto-evaluation and auto-prompt generation techniques.
- Lead initiatives on LLM Agents, RAG, inference optimization (quantization, pruning), and low latency serving
- Evaluate model safety, fairness, and bias—drive AI guardrails and responsible AI development
- Influence roadmap by aligning AI capabilities with product vision and customer needs
- You will help the team leverage your expertise, by coaching and mentoring.
Expectations
- Recognized expert in ML and generative AI—strong research and hands-on experience
- Demonstrates thought leadership in AI strategy and architectural decision-making
- Builds and mentors cross-functional teams
- Drives long-term innovation, reusability, and platform thinking across org
Basic Qualifications
- Experience with SQL
- Experience with R, Python, Weka, SAS, Matlab or other statistical/machine learning software
- Bachelor's degree in a quantitative field, or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience demonstrating strong analytical abilities and confidence in the use of data
- Experience communicating results to senior leadership, or experience in solving complex business challenges by delivering accurate and timely financial models, analysis, and recommendations that have a proven impact on business (e.g., financial savings, operational improvements, or customer benefits)
- 5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Experience working cross functionally with tech and non-tech teams
Preferred Qualifications
- Master's degree, or Master's degree and 3+ years of practical machine learning experience
- Diverse experience will be favored eg. a mix of experience across different roles - In-depth understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service - Technical expertise, experience in AI/ML and GenAI
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