Senior Applied Scientist

Job Description

DESCRIPTION

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). 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.

Key job responsibilities
As a Senior Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Senior Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

BASIC QUALIFICATIONS

- 1. 2+ years of relevant applied science research experience with PhD or 5+ years of experience of applied research experience with a Masters degree in Electrical Engineering, Computer Science, Computer Engineering, Mathematics, or related field with specialization in machine learning, NLP, Computer Vision, deep or related fields.
- 2. Should be an expert in either Computer Vision or NLP and have a good understanding of the both.
- 3. Strong working knowledge of programming languages such as C/C++, Java, or Python.
- 4. Proven ability to relate to and solve business problems through machine learning, data mining and statistical algorithms
- 5. Published and/or presented papers at ACL, ICML, NIPS, KDD, CVPR or similar top-tier conferences and events.
- 6. Technical fluency comfort understanding and discussing architectural concepts and algorithms, schedule trade-offs and new opportunities with technical team members.
- 7. Strong problem solving skills
- 8. Excellent communication skills

PREFERRED QUALIFICATIONS

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

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