Sr. AI/ML Business Solutions Scientist, RBS Availability

DESCRIPTION

Role Overview: We're seeking a senior technical leader to drive the development and scaling of advanced product matching and selection systems. This role will lead technical initiatives addressing a multi-billion dollar market opportunity in retail technology, focusing on improving product discovery and selection coverage.
Key job responsibilities Technical Architecture & Development (60%): Design and implement dual-layer machine learning systems combining state-of-the-art models Develop scalable data pipelines processing 600M+ products monthly Create automated validation frameworks with 99.9% accuracy Build real-time monitoring systems handling 10M+ daily queries Technical Objectives: Improve visual similarity matching from 32% to >70% across categories Develop automated trend detection using advanced AI/ML models Create clustering algorithms for 2000+ product types across multiple regions Manage technical dependencies across multiple engineering and science teams Success Metrics: Achieve >70% accuracy in product matching across categories Drive 60% improvement in processing efficiency Scale systems to handle 2x current capacity by Q4'26 Technical Requirements: Machine Learning & AI: Expert knowledge of machine learning models and frameworks Experience with computer vision and similarity algorithms Proficiency with Large Language Models Strong background in clustering algorithms Data Engineering: Experience with large-scale data pipelines Distributed computing systems expertise Real-time processing system design Data validation frameworks System Architecture: Modular architecture design Microservices architecture API design and development Performance optimization Scalable system design Leadership & Collaboration: Technical project leadership Cross-team collaboration Architecture governance Technical documentation Mentoring and guidance Required Qualifications: 8+ years of software development experience 5+ years of machine learning and data science experience 3+ years leading complex technical projects Bachelor's degree in Computer Science or related field Experience with large-scale distributed systems Track record of improving system performance metrics Preferred Qualifications: Master's degree in Computer Science, Machine Learning, or related field Experience with retail technology systems Previous experience with visual similarity algorithms Track record of successful large-scale system implementations Impact: This role will be instrumental in transforming our product discovery capabilities, directly impacting customer experience and business growth in the competitive retail technology space. A day in the life Key Technical Activities: Lead architectural decisions for ML systems and data pipelines Review and optimize model performance metrics Analyze system health and scalability metrics Develop technical specifications and proof of concepts Debug complex production issues Evaluate and approve architecture changes Design solutions for improving visual similarity algorithms Leadership & Collaboration: Lead technical design reviews and architecture syncs Mentor team members on ML best practices Collaborate with data scientists on model improvements Align with cross-functional teams on technical dependencies Guide implementation strategies across multiple teams Review and approve technical proposals Provide architectural guidance for scaling solutions Strategic Focus: Drive improvements in model accuracy and system performance Define technical standards and best practices Balance immediate technical needs with long-term architecture Evaluate new ML technologies and approaches Guide innovation in automated trend detection Ensure system reliability and scalability Monitor and improve key performance metrics Regular Interactions: ML Engineers and Data Scientists Product and Platform teams Infrastructure teams Business Intelligence teams Senior technical leadership This role combines hands-on technical expertise in ML/AI with strategic architectural leadership, requiring both deep technical knowledge and strong collaboration skills. The focus is on driving technical excellence while ensuring successful delivery of large-scale ML solutions that impact business metrics. About the team The RBS-Availability program includes Selection Addition (where new Head-Selections are added based on gaps identified by Selection Monitoring-SM), Buyability (ensuring new HS additions are buyable and recovering established ASINs that became non-buyable), SoROOS (rectify defects for sourceble out-of-stock ASINs ) Glance View Speed (offering ASINs with the best promise speed based on Store/Channel/FC level nuances), Emerging MPs, ASIN Productivity (To have every ASINS actual contribution profit to meet or exceed the estimate). The North-Star of the Availability program is to "Ensure all customer-relevant (HS) ASINs are available in Amazon Stores with guaranteed delivery promise at an optimal speed." To achieve this, we collaborate with SM, SCOT, Retail Selection, Category, and US-ACES to identify overall opportunities, defect drivers, and ingress across forecasting, sourcing, procurability, and availability systems, fixing them through UDE/Tech-based solutions.

BASIC QUALIFICATIONS

• 5+ years of SQL experience
• Experience programming to extract, transform and clean large (multi-TB) data sets
• Experience with theory and practice of design of experiments and statistical analysis of results
• Experience with AWS technologies
• Experience in scripting for automation (e.g. Python) and advanced SQL skills.
• Experience with theory and practice of information retrieval, data science, machine learning and data mining

PREFERRED QUALIFICATIONS

• Experience working directly with business stakeholders to translate between data and business needs
• Experience managing, analyzing and communicating results to senior leadership