Sr. AI/ML Business Solutions Scientist, RBS Availability

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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.

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• 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
  

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• 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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