ADCI - BLR
Applied Science, cx and business trends
AppliedScientistII
Neural analysis suggests this role is
optimal for Mid candidates.
“Applied Scientist II at ADCI - BLR. Skills: GenAI, NLP, Computer Vision, Machine Learning. Design scalable GenAI solutions. Deploy scalable GenAI solutions”
Industry & Context.
Problem solving
What They're Looking For.
Must Have
1 year relevant applied research experience with PhD, 3+ years relevant applied research experience with Masters, Expert in Computer Vision or NLP, Good understanding of both CV and NLP
Nice to Have
Post Graduate degree in EE, CS, Maths or Physics, Specialization in ML, NLP or Computer Vision, Scientific thinking, Track record of thought leadership, Solid understanding of ML/DL algorithms, CS fundamentals in data structures, CS fundamentals in problem solving, CS fundamentals in algorithm design, CS fundamentals in complexity analysis
What You'll Do.
Design scalable GenAI solutions
Deploy scalable GenAI solutions
Design scalable NLP solutions
Deploy scalable NLP solutions
Design scalable Computer Vision solutions
Deploy scalable Computer Vision solutions
Develop novel LLM techniques
Develop deep learning techniques
Develop statistical techniques
Define research strategy
Define experiments strategy
Partner with business teams
Partner with engineering teams
Identify complex problems
Solve complex problems
Leverage team expertise
Contribute to professional development
Improve technical knowledge
Improve engineering practices
Guide team to file patents
Guide team to publish research
Impact product strategy
Identify new business opportunities
Provide strategic direction
How You'll Work.
Team & Collaboration
Business teams; Engineering teams; Research teams; Technical teams
Communication Scope
Excellent communication; Verbal communication; Written communication
Full Job 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 an 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 developme
Applying for this Applied Scientist II role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
ANONYMOUS · UNFILTERED
What do employees actually say about ADCI - BLR?
Real rants from real employees. Read before you apply.