Atul Yadav

End-to-end ML solutions from ideation to production, collaborating with cross-functional teams across operations and commercial functions, delivering 22% efficiency gains and £80K+ annual cost savings. Built production ML infrastructure serving 1000+ daily predictions with automated CI/CD, drift detection, performance tracking, and governance controls while achieving 15% process improvement. Secured £200K+ in project funding by presenting technical solutions to senior leadership and external partners, translating complex ML approaches into compelling business cases. Deployed scalable real-time inference systems for complex operational processes using Python and Azure, maintaining 99% uptime and reducing manual error rate by 70%. Processed and analyzed large-scale datasets using SQL and Python to extract actionable insights, building automated ETL pipelines that integrated multiple data sources into centralized PostgreSQL databases. Designed a customer analytics platform tracking user

Architected and deployed 5+ production ML models via Flask APIs, automating statistical analysis workflows and reducing decision-making time by 35%. Engineered automated testing and documentation frameworks, improving code quality and reducing deployment errors by 40%. Mentored a team of junior ML engineers in PyTorch implementation, code review processes, and production deployment strategies.

Delivered 4+ client-facing apps and dashboards, gaining experience in frontend and Android development before transitioning into AI/ML engineering.