Sohum Sukhatankar — Resume

S.M. in Computer Science

A.B. in Computer Science and Mathematics

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February 2022 – Current • New York, NY

• Founding team member (#4), currently leading Special Projects.
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• eeeeee serverless HTTP stack, distributed TLS relays, container sandboxing via gVisor, eBPF network infrastructure, and a WireGuard-based VPN.
• I started engineering work on the modal.com website.
• hhhhhj

Contract Software Engineer at Prosper Robotics

January 2022 • London, UK

• Early-stage startup developing VR-teleoperated household robots. Worked with electrical and mechanical engineers.
• I wrote real-time (<10 μs) embedded microcontrollers in C++, developed new network services and robot control systems in Go. Refactored a lot of code, fixed many bugs, ported software to a new robot, introduced continuous integration, tests, static type checking for Python.

Software Engineer at Convex

June 2021 – October 2021 • San Francisco, CA

• First hired engineer at a seed-stage startup. Worked with three experienced technical cofounders (ex-principal engineers at Dropbox) to build a reactive, serverless database platform using Rust, integrated with the V8 JavaScript engine.
• Wrote significant components of the MVP. As an early core team member, this included rearchitecting the entire Convex client library, writing several systems components in Rust, and advising on developer experience.

Quantitative Research Intern at Jump Trading

June 2021 – August 2021 • Chicago, IL

• Won the intern trading strategies competition and rotated on a trading team to research algorithmic signals in US equities.
• Developed decentralized apps on the Ethereum blockchain for the cryptocurrency team, including new trading algorithms on DEXs. Contributed to the open source Ethereum ecosystem in Rust, Go, and Python.

Software Engineering Intern at Scale AI

December 2020 – January 2021 • San Francisco, CA

• Worked on machine learning infrastructure for a fast-growing startup using Terraform, Kubernetes, and AWS.
• Developed an in-house system to unify the ML training workflow, allowing the team to quickly iterate on models, share results on a tracking server, and launch Kubernetes distributed training jobs, saving “hours” of time on each experiment.

Architecture Intern at Nvidia

June 2020 – August 2020 • Santa Clara, CA

• Worked with the Applied Deep Learning Research (ADLR) group on deep learning models for street image segmentation.
• Individually developed and released FastSeg, an open-source library containing state-of-the-art PyTorch implementations of MobileNetV3 LR-ASPP for real-time semantic segmentation, significantly more accurate than existing public implementations.

Computer Science:

• International Olympiad in Informatics (IOI): Gold Medalist (2018, 2019), 7^th place globally
• Google Hash Code: World Finalist (2020, 2021, 2022), 6^th place team out of over 100,000 students and professionals
• Google Code Jam: Round 3 Finalist (2020), placed 34^th globally
• Facebook Hacker Cup: Round 3 Finalist (2020)
• PicoCTF: Winner (2018), ranked 6th

Mathematics:

• Mathematical Olympiad Program (MOP): Participant (2017), IMO team selection group (2017, 2018)
• USA Math Olympiad (USAMO): Honorable Mention (2017), top 24 in nation

Physics:

• U.S. Physics Team: Invitee (2017, 2018, 2019)
• USA Physics Olympiad (USAPhO): Gold Medalist (2017, 2018, 2019)

Music Performance:

• National YoungArts Foundation: Winner in Classical Music (2018, 2019)
• JDR Viola Competition: Grand prize winner, performed with a professional orchestra (2019)
• Texas All-State Symphony Orchestra: Principal Violist (2017), Co-Principal (2016, 2018)