Saurabh Das
VP Of Engineering at HyperTrack
Mumbai, Maharashtra, United States
Summary
👤
Senior🎓
Top SchoolSaurabh Das is a founder and technical leader with 11 years of experience building high-performance trading systems, ML-driven products, and real-time infrastructure across startups and finance. As CTO of Silverleaf Capital Services he architected ultra-low latency trading platforms (sub-2 µs paths and FPGA implementations), scaled teams and systems that processed ₹20B daily while delivering sustained double-digit returns and industry-leading risk metrics. He thrives in zero-to-one environments—taking ideas through data-driven experimentation, rapid iteration, and production rollouts—and has repeatedly improved testing velocity and cost efficiency by orders of magnitude. At HyperTrack he led real-time location and logistics intelligence that improved fleet efficiency, worker income, and carbon outcomes for global customers. A hybrid of engineer, scientist and operator, he combines deep systems and ML expertise with empathetic leadership and a strong bias for written communication and mentorship. Based in Mumbai with an IIT Bombay and IIM Ahmedabad background, he has a rare track record of applying advanced ML/RL in adversarial, high-stakes production settings.
11 years of coding experience
12 years of employment as a software developer
Master of Business Administration - MBA (PGDM), Master of Business Administration - MBA (PGDM) at Indian Institute of Management, AhmedabadIndian Institute of Technology Bombay
Github Skills (75)
categories10
levenshtein-distance10
metaprogramming10
lexical-analysis10
phonetics10
intervals10
aws-s310
ack10
concurrency10
memory-allocation10
combinatorics10
commons10
polymorphism10
charset10
ranges10
Programming languages (3)
Github contributions (5)
saurabhdas/java-to-d
Jul 2016 - Jan 2019
Contributions:16 commits, 2 PRs, 13 pushes in 2 years 6 months
javajniparseparser
silverleafcaps/iceberg
May 2018 - Oct 2020
ML Base Layer
Contributions:1 review, 10 PRs, 145 pushes in 2 years 5 months
machine-learning
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