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 responsibilitiesTechnical Architecture & Development (60%):Design and implement dual-layer machine learning systems combining state-of-the-art modelsDevelop scalable data pipelines processing 600M+ products monthlyCreate automated validation frameworks with 99.9% accuracyBuild real-time monitoring systems handling 10M+ daily queries
Technical Objectives:
Improve visual similarity matching from 32% to >70% across categoriesDevelop automated trend detection using advanced AI/ML modelsCreate clustering algorithms for 2000+ product types across multiple regionsManage technical dependencies across multiple engineering and science teams
Success Metrics:
Achieve >70% accuracy in product matching across categoriesDrive 60% improvement in processing efficiencyScale systems to handle 2x current capacity by Q4'26
Technical Requirements:
Machine Learning & AI:Expert knowledge of machine learning models and frameworksExperience with computer vision and similarity algorithmsProficiency with Large Language ModelsStrong background in clustering algorithms
Data Engineering:
Experience with large-scale data pipelinesDistributed computing systems expertiseReal-time processing system designData validation frameworks
System Architecture:
Modular architecture designMicroservices architectureAPI design and developmentPerformance optimizationScalable system design
Leadership & Collaboration:
Technical project leadershipCross-team collaborationArchitecture governanceTechnical documentationMentoring and guidance
Required Qualifications:
8+ years of software development experience5+ years of machine learning and data science experience3+ years leading complex technical projectsBachelor's degree in Computer Science or related fieldExperience with large-scale distributed systemsTrack record of improving system performance metrics
Preferred Qualifications:
Master's degree in Computer Science, Machine Learning, or related fieldExperience with retail technology systemsPrevious experience with visual similarity algorithmsTrack record of successful large-scale system implementationsImpact: 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 pipelinesReview and optimize model performance metricsAnalyze system health and scalability metricsDevelop technical specifications and proof of conceptsDebug complex production issuesEvaluate and approve architecture changesDesign solutions for improving visual similarity algorithms
Leadership & Collaboration:
Lead technical design reviews and architecture syncsMentor team members on ML best practicesCollaborate with data scientists on model improvementsAlign with cross-functional teams on technical dependenciesGuide implementation strategies across multiple teamsReview and approve technical proposalsProvide architectural guidance for scaling solutions
Strategic Focus:
Drive improvements in model accuracy and system performanceDefine technical standards and best practicesBalance immediate technical needs with long-term architectureEvaluate new ML technologies and approachesGuide innovation in automated trend detectionEnsure system reliability and scalabilityMonitor and improve key performance metrics
Regular Interactions:
ML Engineers and Data ScientistsProduct and Platform teamsInfrastructure teamsBusiness Intelligence teamsSenior technical leadershipThis 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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Company
- ADCI MAA 15 SEZJob ID: A3047838
