Summary
Daksh Jotwani is an experienced software engineer with nine years building embedded, cloud, and autonomy systems across Tesla and Applied Intuition. He blends a rigorous Computer Science and Mathematics background from Purdue (3.94 GPA) with hands-on work in OS, Linux updaters, networking for energy products, and distributed vehicle-cloud services including WebRTC streaming and OTA updates. At Applied Intuition he now focuses on motion planning and controls for L2+ self-driving systems, bringing production-grade safety and real-time constraints to complex stacks. His tenure at Tesla spans from intern to senior engineer, giving him deep familiarity with scaling firmware and infrastructure for Megapacks, Powerwalls, and Superchargers. Based in San Francisco, he pairs systems-level thinking with applied math, often operating at the intersection of control theory and cloud-connected vehicle services. Colleagues rely on him to translate algorithmic ideas into robust, deployable software for safety-critical domains.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS Mathematics and Computer Science, Bachelor of Science - BS Mathematics and Computer Science at Purdue University
Greenwood High International School
Spanish, Hindi, English