Aditya Saxena — Lead ML Engineer

Software Engineer with interests in distributed systems architecture, large scale data processing, ML model deployment, and cross-platform development to build systems that process and derive meaningful insights from data at enterprise scale. Current and past projects: • Architected a large-scale Gen AI media generation platform that reduced 2D generative media content creation costs by 65% and decreased production time from weeks to hours. • Designed microservice architecture for automated 2D image and video generation across 5 product types using AWS SageMaker, Step Functions, and ECS, scaling to process 100K+ assets daily. • Built robust supplier data ingestion pipeline using Apache Spark and AWS services (S3, Lambda, DynamoDB and DocumentDB), handling terabytes of varied media formats with 99.9% reliability. • Implemented intelligent quality assurance system using machine learning models that automatically validated 95% of generated assets, reducing manual review requirements by 40%. • Created comprehensive data observability solution using AWS Glue Tables, CloudWatch and in-house tools with custom dashboards, enabling monitoring of asset generation pipelines across multiple AWS accounts and regions. • Developed enterprise-wide integration testing framework for ML models that standardized testing methodologies across teams, reducing regression issues and improving verification throughput by 3x and accelerating model deployment. • Designed and implemented standardized framework for productionizing ML Models as SageMaker inference pipelines, decreasing time-to-production from 8 weeks to 2 weeks and significantly reducing technical debt. • Worked with applied scientists to productionize and deploy ML models on distributed systems to automate image creation for apparel products, delivering measurable glance-view-coverage gains across multiple product categories. • Engineered mobile-responsive layout for multiple web pages with complex UI components including collection summary, filters, and edition cards, improving customer engagement metrics by 22%. • Led cross-functional initiative to integrate functionality of product variations display, enhancing the shopping experience across desktop and mobile. • Architected and implemented system-wide central storage solution using Rust supporting 20+ Android and Linux based applications across thousands of Amazon Alexa devices, enabling standardized data management and seamless OS migration.

Stackforce AI infers this person is a Software Engineer specializing in Machine Learning and Cloud Solutions for enterprise-scale applications.

Location: Seattle, Washington, United States

Experience: 10 yrs 1 mo