Sashankh Kumar is a generalist software and machine learning engineer with a decade of experience building scalable ML platforms and production data systems across fintech and research environments. Currently focused on ML platform work in the Bay Area, he has designed and deployed large-scale recommendation and inference systems using GNNs, PyTorch DDP/FSDP, Spark, Airflow and serving stacks like Cassandra and DuckDB. His background spans full-stack product delivery—interactive audience-builder UIs, observability pipelines to Prometheus/Grafana, and microservices—paired with hands-on ML ops for model training and GPU infrastructure. A Georgia Tech MS student and NUS alumnus who has shipped annotation and RAG-based conversational agents for medical use cases, he combines rigorous academic training with enterprise-grade engineering. Notably, he has worked end-to-end from data transformations to low-latency serving for billions-of-records use cases, showing a rare comfort with both system design and model-centric engineering.
10 years of coding experience
5 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Georgia Institute of Technology
Exchange Student, Computer Science, Exchange Student, Computer Science at ETH Zürich
Bachelor in Computing (Honours), Computer Science, Bachelor in Computing (Honours), Computer Science at National University of Singapore
Contributions:4 PRs, 23 pushes, 3 branches in 5 years 2 months
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