Sr. AI/ML Business Solutions Scientist, RBS Availability
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
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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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