Robotics Software Engineer

Pebble•Fremont, CA

3d•$111,000 - $141,000•Onsite

About The Position

Pebble is a sustainable living startup defining a new way to live, work, and explore from anywhere with a 100% electric, hassle-free RV trailer. Built by experts in automotive and consumer technology, Pebble combines electrification with cutting-edge intelligent systems to remove the hassles RV owners have endured for decades. At Pebble, we are building the future of lighter, more flexible living. We see a world where your home can be anywhere you want it to be. If that idea sparks your imagination, we'd love to meet you. We are looking for a curious and driven new grad Robotics Software Engineer to join our vehicle intelligence team. In this role you will work across the full robotics stack from sensor drivers and perception pipelines to planning, control, and AI-powered agent workflows on our all-electric Pebble Flow travel trailer platform. You will work closely with senior engineers and cross-functional teams to bring intelligent autonomy features to life in a real production vehicle. This role is ideal for a recent graduate or early-career engineer who has strong fundamentals in robotics systems and a genuine interest in applying AI agent workflows to real-world vehicle automation challenges. This is an onsite position at our Fremont, CA headquarters. No remote or hybrid work.

Requirements

Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or a related field.
Solid understanding of robotics fundamentals: kinematics, sensor fusion, state estimation, motion planning, and feedback control.
Proficiency in Python and C++; ability to write production-quality code in both.
Demonstrated experience with AI agent frameworks (LangGraph, LangChain, AutoGen, or equivalent) — this is a must.
Understanding of LLM tool-use patterns: function calling, structured outputs, and multi-step agentic reasoning.
Familiarity with Linux development environments, Git, and CI/CD workflows.

Nice To Haves

Experience with simulation environments such as Gazebo, Isaac Sim, CARLA, or similar.
Familiarity with computer vision libraries (OpenCV, PyTorch, or similar) for perception tasks.
Exposure to embedded or real-time software development (RTOS, CAN bus, microcontrollers).
Interest in or experience with electric vehicle systems, autonomous features, or ADAS.
Prior work with multi-agent orchestration systems that interface with physical hardware.

Responsibilities

Develop and maintain software across the full robotics stack: perception, localization, mapping, planning, and control.
Implement and integrate sensor drivers and fusion pipelines for GPS/GNSS, IMU, cameras, ultrasonic, and other vehicle sensors.
Build motion planning and trajectory control algorithms for automated vehicle maneuvers (e.g., auto-hitch, auto-park, auto-dump).
Contribute to real-time control loops running on embedded compute platforms with strict timing and safety requirements.
Write, test, and debug nodes, topics, services, and actions.
Hands-on experience with ROS or ROS 2: writing nodes, using standard message types, debugging with rqt/rviz.
Design and implement AI agent workflows that orchestrate multi-step reasoning and action across vehicle subsystems.
Integrate LLM-based agents (e.g., LangGraph, LangChain, or custom frameworks) with robotics middleware to enable natural-language-driven automation.
Develop tool-use and function-calling interfaces that allow AI agents to safely interact with vehicle APIs, sensor streams, and cloud services.
Collaborate with the AI/data platform team to connect on-vehicle agent workflows with cloud-side analytics and fleet intelligence systems.
Write clean, well-tested, and well-documented code; participate in code reviews and contribute to team coding standards.
Develop unit tests, integration tests, and simulation-based validation using tools such as Gazebo, Isaac Sim, or equivalent.
Debug field issues using telemetry, log analysis, and on-vehicle testing.
Work closely with hardware, embedded software, and product teams to ensure seamless HW/SW/AI integration.
Engage in agile development sprints, contribute to technical design discussions, and document findings in Confluence or equivalent.