# Nitish Sanghi > Robotics & Autonomy | Production-Scale, Safety-Critical Systems Location: San Francisco Bay Area, United States Profile: https://flows.cv/nitishsanghi I’m a robotics and autonomy engineer with 12+ years of experience building and deploying production, safety-critical systems across medical robotics, autonomous vehicles, and industrial automation. I spent seven years at Intuitive Surgical working on FDA-regulated robotic platforms used in live clinical environments, where reliability, validation, and real-world constraints were non-negotiable. More recently, I’ve worked on autonomy software at Cruise and other AV companies, integrating perception and autonomy stacks with real vehicles operating in complex environments. Across hardware and software, my work consistently sits at the system boundary, where safety, deployment, and scale dominate architectural decisions. That perspective now shapes the problems I spend time exploring: autonomy and robotics systems that are designed for real-world operation, not demos. I’m particularly interested in technically hard problems where first-principles thinking, system-level design, and long-term reliability create durable advantages. ## Work Experience ### Senior Software Engineer — Autonomy Perception @ Cyngn Jan 2024 – Present | Menlo Park, California, United States Led production deployment of core perception systems for safety-critical industrial autonomous vehicles, spanning LiDAR ground segmentation, dynamic occupancy representations, and fail-operational diagnostics. Improved real-world object detection performance and enabled smoother, more reliable trajectory generation in dense industrial ODDs. Built the evaluation and verification infrastructure required to ship safely, including a metrics framework and simulation-driven V&V across Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), and Hardware-in-the-Loop (HIL) testing, enabling early detection of regressions and real-world failure modes. Owned production readiness end-to-end, from requirements coverage and simulation-based validation to long-term maintainability, reducing technical debt and increasing unit test coverage. ### Senior Software Engineer — Autonomous Software Integration @ Cruise Jan 2023 – Jan 2024 | San Francisco Bay Area Fully autonomous urban vehicles (Origin platform) Worked on integration and production deployment of autonomy software for the Cruise Origin, a purpose-built, driverless vehicle operating in dense urban environments. Owned end-to-end integration of the autonomy stack with vehicle hardware, spanning simulation, bench testing, closed-course validation, and limited public-road operation. This included bringing up new releases on real vehicles, diagnosing cross-stack failures, and resolving hardware–software coupling issues that only emerge at system scale. I also managed and optimized the production launch pipeline for autonomy releases, enabling repeatable, safe bring-up of perception and autonomy components under constrained, safety-critical operating modes. ### Software Engineer — Autonomous Systems (Safety & Redundancy)* @ Argo AI Jan 2022 – Jan 2022 | Palo Alto, California, United States *Impacted by company shutdown in December 2022. Worked on safety-critical autonomy systems focused on redundancy and fail-operational behavior for autonomous vehicles. Designed and optimized components of a redundant AV stack intended to safely take over when the primary autonomy system degrades or fails, with emphasis on perception robustness and predictable system behavior under fault conditions. Integrated high-density custom LiDAR data (~900k points per sweep) into ground surface estimation pipelines, improving perception accuracy while reducing average runtime from 42 ms to 18 ms to meet real-time constraints. Built internal tooling to visualize and debug ground estimation outputs and failure cases directly from raw LiDAR streams. This work reinforced the importance of designing autonomy systems that degrade gracefully, expose failure early, and remain predictable under partial system loss. ### Engineer / Lead Mechanical Engineer — Advanced Energy Systems @ Intuitive Jan 2015 – Jan 2022 | Sunnyvale, California, United States FDA-regulated robotic surgical platforms Spent seven years building and scaling FDA-regulated, safety-critical robotic systems used in live clinical environments, where design errors translate directly to patient risk, recalls, or production shutdowns. Led mechanical design and production validation for next-generation advanced energy surgical systems, owning end-to-end development from early architecture through design verification, validation, and manufacturing scale-up. This included thermal management of power electronics, durability and safety testing (shock, vibration, thermal, fluid ingress), and close vendor collaboration to ensure DfMA and production robustness. In parallel, worked on sustaining engineering and supply-chain resilience for advanced energy instruments in active clinical production, including COVID-era supply disruptions. Built internal quality analytics to identify systemic failure modes, prioritize high-risk components, and drive continuous quality and cost improvements across multiple product lines. This experience shaped my approach to building physical systems: assume failure, validate aggressively, and design for scale and long-term reliability, not just first launch. ### Graduate Student Researcher @ University of Michigan Jan 2020 – Jan 2020 | Ann Arbor, Michigan, United States ▪ Developed a Human Gait State Estimator for Prostheses based on an EK filter which was able to successfully estimate the gait state with 98.5% accuracy of 10 test subjects. ### Mechanical Engineer — Automation, Systems & Reliability @ Cogenra Solar Jan 2013 – Jan 2015 | San Francisco Bay Area Projects — Automation, Systems Design & Reliability Built and deployed end-to-end automation and robotic systems for solar and industrial applications, spanning mechanical design, controls, vision, and production testing. Designed and delivered semi-automated robotic assembly and inspection systems under aggressive timelines, including Cartesian robot integration for precision adhesive dispensing, inline vision inspection using Python/OpenCV, and automated thermal cycling test infrastructure with data collection and analysis. These systems were deployed in production and pilot-scale environments, including a 1 MW solar power plant. In parallel, led system-level thermal and reliability engineering efforts for multiple generations of photovoltaic and cogeneration platforms, including actively cooled substrates, liquid cooling systems, and thermal safety components taken from design through analysis (FEA), validation, and production. This work established an early foundation in designing physical systems where reliability, manufacturability, and real-world constraints dominate architectural decisions. ### Graduate Teaching Assistant (Computer Science) @ University of Illinois Urbana-Champaign Jan 2013 – Jan 2013 | Urbana-Champaign, Illinois Area ▪ Conducted labs for undergrad students in “Intro to CompSci. and Programming in JAVA” ▪ Guided students and supervised course assistants in programming concepts ### Research Assistant, Aerospace Robotics and Control Group (ARCG) @ University of Illinois Urbana-Champaign Jan 2011 – Jan 2013 | Urbana-Champaign ▪ Designed artificial muscle actuators using Electro-active Polymers ▪ Fabricated flexible robotic manipulators with redundant DOFs and tested for feasibility ▪ Worked on controller design for manipulator using nonlinear oscillators ▪ Implemented control simulations in Matlab and Simulink ### Graduate Teaching Assistant (Mechanical Engineering) @ University of Illinois Urbana-Champaign Jan 2011 – Jan 2012 | Urbana-Champaign, Illinois Area - Taught lab sections of 20+ undergrad students in Engineering Materials Mechanical Properties - Conducted material testing and guided students through experiments ### Undergraduate Researcher @ Indian Institute of Technology, Delhi Jan 2008 – Jan 2010 | New Delhi Area, India Undergraduate Research & Capstone Projects — Mechanical & Robotic Systems Completed multiple end-to-end engineering projects spanning fluid dynamics, energy systems, robotics, and human-centered mechanical design, taking concepts from first-principles modeling through simulation, prototyping, and physical testing. Projects included computational analysis and redesign of centrifugal pumps using CFD, development and fabrication of a downdraft gasifier stove based on mathematical flow modeling, synthesis and prototyping of under-actuated robotic grippers, and design of a low-cost prosthetic knee joint with gait-driven locking mechanisms. These projects established an early foundation in first-principles modeling, simulation-driven design, and building physical systems under real-world constraints. ### Graduate Engineering Intern — Vehicle Safety Systems @ Tata Motors Jan 2009 – Jan 2009 | Pune, Maharashtra, India Worked on evaluation and validation of automotive safety-critical systems, including airbag restraint algorithms and occupant protection mechanisms. Analyzed crash test data and reviewed ECU calibration and deployment logic for restraint systems, gaining early exposure to how safety algorithms are validated against real-world impact scenarios. In parallel, contributed to seat system safety evaluation by developing design validation plans, performing failure mode and effects analysis (FMEA), and running structural simulations to assess performance under crash loads. This experience reinforced a foundational understanding of safety verification, failure analysis, and validation-driven design in systems where timing, reliability, and edge cases directly affect human safety. ## Education ### Master of Science - MS in Robotics University of Michigan ### Master of Science - MS in Mechanical Engineering University of Illinois Urbana-Champaign ### Bachelor of Technology in Mechanical Engineering Indian Institute of Technology, Delhi ## Contact & Social - LinkedIn: https://linkedin.com/in/nitishsanghi - Website: https://www.nitishsanghi.com --- Source: https://flows.cv/nitishsanghi JSON Resume: https://flows.cv/nitishsanghi/resume.json Last updated: 2026-04-01