Aakaash Jois

Machine learning engineer and applied scientist with 5+ years of experience building scalable, production-grade ML systems across adtech and insurtech with specialization in multimodal modeling, NLP, and ML platform engineering, and deep experience owning solutions from data ingestion to deployment. At Microsoft, I lead initiatives that improve ad quality and content safety at massive scale, designing models, optimizing pipelines, and modernizing infrastructure with a focus on system simplification, throughput, and reliability. I’ve delivered ML systems that integrate across image, text, and video, working closely with infra, product, and research teams to ship solutions that matter. Previously at Xandr and Kalepa, I built ML platforms from the ground up, designing model architectures, developing custom data workflows, and deploying inference at scale using tools like Azure ML, Kubernetes, and SageMaker. I’ve worked across CV, NLP, and explainability, and enjoy solving ambiguous problems where ML meets systems engineering. I thrive in environments where I can own high-impact problems end-to-end, mentor others, and help teams scale fast without compromising quality.