# Massi Amrouche > Software Engineer, Planner Reasoning Foundations Location: San Francisco Bay Area, United States Profile: https://flows.cv/massi Software engineer with over 4 years of hands-on experience in building software for robotics and autonomy. I worked on various aspect of the robotics autonomy stack with recent experience in perception and behavior. I take pleasure in optimizing the robotics stack, and I have a keen interest in reducing latencies to enhance system efficiency. Research experience in vision-based collision avoidance in uncertain environments for autonomous vehicles. Experience in developing novel approaches in deep learning theory for sequence-to-sequence tasks with recent publications. ## Work Experience ### Software Engineer, Planner Reasoning Foundations @ Waymo Jan 2025 – Present | Mountain View, California, United States Building autonomy for Waymo’s ride-hailing platform within the Planner Reasoning Foundations team. ### Software Engineer, Motion Planning & Prediction @ Kodiak Jan 2024 – Jan 2025 | Mountain View, California, United States Building autonomy for semi-trailer trucks ### Software Engineer, Robotics/ML @ Skyways Jan 2023 – Jan 2024 | Austin, Texas, United States Building autonomy for Unmanned Aerial Vehicles ### Software Engineer, Motion Behavior @ Nuro Jan 2022 – Jan 2023 | Mountain View, California, United States Building autonomy for cars. ### Robotics Engineer @ Vicarious Jan 2021 – Jan 2022 | San Francisco Bay Area Building autonomy for robotics arms. Vicarious was acquired by Alphabet and merged with Intrinsic AI. ### Teaching Assistant @ University of Illinois at Urbana-Champaign Jan 2018 – Jan 2021 | Région de Urbana-Champagne, Illinois, États-Unis Taught classes: • Robot Dynamics and Control** (ME446): Introduction to the fundamental concepts and analytical methods for analysis and design of robot systems. • Analysis of Nonlinear Systems (ECE 528): Nonlinear dynamics, vector fields and flows, Lyapunov stability theory, regular and singular perturbations, averaging, integral manifolds, input-output and input-to-state stability, and various design applications in control systems and robotics. • State Space Design for Control (SE424): Design methods; time domain modeling; trajectories and phase plane analysis; similarity transforms; controllability and observability; pole placement and observers; linear quadratic optimal control; Lyapunov stability and describing functions; simulation. • Control Systems (SE320): Introductory class to the control theory and application. The class spans different area of control. • Design and Anlysis of Experiments (IE400): Introductory class to the statistical analysis of physical experiments via analysis of variance (ANOVA) using the statistical software SAS. ** Figured on the list of TAs ranked as excellent by their students. ### Graduate Research Assistant @ Coordinated Science Laboratory at University of Illinois Jan 2016 – Jan 2021 | Région de Urbana-Champagne, Illinois, États-Unis Control theory, path planning, collision avoidance, dynamical games, recurrent neural networks (LSTM, GRU), Reinforcement Learning. ### Machine Learning Scientist Intern @ NIO Jan 2019 – Jan 2019 | San Francisco Bay Area In the planning group, working on trajectory prediction for Autonomous Driving. Keywords: autonomous driving, deep learning, trajectory prediction. ### Software Engineering Intern @ Dassault Systèmes Jan 2015 – Jan 2015 | Vélizy-Villacoublay, France I was in a group in charge of developing a real-time ”experience-oriented” engine, leveraging all together multi-threading, multi-processing, distributed key-value memory, and scripting. My contribution/task was to develop a massively distributed numerical simulation using the real-time engine developed by the team for the purpose of testing its scalabilty. Keywords: C++, multi-threading, multi-processing, agile methods, script engines, real time simulations. ### Research Intern @ Center for Applied Research IRC-ESTP Paris Jan 2014 – Jan 2014 | Région de Paris, France Worked in a research team on : • Smoothed Particles Hydrodynamics (SPH) schemes for the compressible Euler equations. • Development of a solver for modeling complex free surface flows using SPH method. • CPU parallelization with MPI. • GPU parallelization using CUDA. Keywords: HPC, MPI, OpenMP, CUDA, Numerical Schemes, SPH. ## Education ### Doctor of Philosophy (PhD) in System Engineering University of Illinois Urbana-Champaign ### Master's degree in Mathématiques appliquées École Normale Supérieure Paris-Saclay ### Double Master degree in Smart Aerospace and Autonomous Systems in Automatic Control and Robotics Poznan University of Technology ### Master of Science (MS) in Smart Aerospace And Autonomous Systems Université Évry Paris-Saclay ## Contact & Social - LinkedIn: https://linkedin.com/in/massi-amrouche-35b772105 --- Source: https://flows.cv/massi JSON Resume: https://flows.cv/massi/resume.json Last updated: 2026-04-11