Jan 2021 – Dec 2023 · 2 yrs 11 mos · Menlo Park, California, United States · Remote

• I was the first employee and founding engineer responsible for all things machine learning and computer vision, and a core member of the team across the entire stack.
• I also made several key architectural and design choices, and contributed as an IC to the codebase, across ML Development, ML Ops, Backend, DevOps, and Frontend.
• These are a few highlights:
• Built and scaled the initial deep learning pipeline and ML models to process several 1000 video clips per minute at state of the art accuracy.
• Worked closely with a team of 2 other ML Engineers to design and implement an ML system that far outperformed state of the art video object detection, built on semi supervised learning with weak object labels, requiring no external annotation services.
• Worked with a senior frontend engineer to completely rearchitect and reimplement the frontend web app, rewriting it in React
• Led several design decisions that resulted in a distributed cloud based system that was highly available and horizontally scalable (built on Kubernetes)
• Worked closely with the Sales and Customer success teams, and directly with customers, functioning as the technical point of contact for several key accounts.
• Set up several processes throughout engineering and customer success as the company scaled from 0 to 1M$ ARR

Apr 2019 – Jan 2021 · 1 yr 9 mos · Palo Alto, California

• Worked on the Store 'Events' Team with Prof. Silvio Savarese, Dr. Chunhui Gu and Dr. Wongun Choi:
• Led the algorithm design, implementation and testing for the 'Events' module
• Responsible for converting video / trajectory data into actionable insights by using data driven and heuristic based approaches to model human behavior, human-object interaction etc.
• Successfully delivered highly performant computer vision algorithms for diverse use cases, in 3 different industry verticals
• Worked on large scale data driven approaches to extract meaningful, business-actionable insights
• Set up processes and systems to ensure code health, perform rigorous testing and follow software development best practices

Jan 2019 – Apr 2019 · 3 mos

• Member of admissions committee for the Computer Science Department MS program for 2020.

Sep 2018 – Apr 2019 · 7 mos

• Head Teaching Assistant for CS230: Deep Learning taught by Prof. Andrew Ng
• Responsible for contributing to, organizing and leading student discussion sections
• Mentored over 50 student team projects from diverse fields
• Designed the midterm evaluation used to assign a significant portion of the course grade
• In charge of all logistic and organizational tasks for a course taken by 400+ students

Apr 2018 – Mar 2020 · 1 yr 11 mos

• Worked in the Stanford Vision Lab with Prof. Silvio Savarese and Dr. Juan Carlos Niebles. Primarily focused on 2D/3D tracking and multimodal sensor fusion. I also spent time working on pedestrian intent prediction. During my time working on these projects, I was able to contribute to two large scale datasets, JRDB and STIP, and 3 publications - 1 in TPAMI, 1 in IROS, and 1 in RAL/ICRA.

Jun 2018 – Sep 2018 · 3 mos · Cupertino, California

• Intern at the CVML team
• Selected as one of only 12 interns to present summer projects to the SVP of Software
• Worked on exploring Generative Modeling approaches

Jun 2015 – Aug 2015 · 2 mos · Bengaluru, Karnataka, India

• Worked with the Test Engineering team at the Schneider Electric Research and Development facility.
• Fully automated a testing process for an LCD display, and laid down the framework for instituting computer vision driven testing processes.