Founding Robotics Engineer

Prevail Recruiting•San Diego, CA

About The Position

Develop robotic and autonomous systems that connect sensing, computation, planning, controls, and physical hardware. The role spans system architecture, algorithm development, embedded integration, simulation, and testing on real platforms. Candidates should bring depth in at least one core robotics discipline and systems knowledge across the full stack, including the ability to derive algorithms, implement production software, diagnose hardware behavior, and validate performance through repeatable experiments. The engineer will own robotics development from concept through deployment, translating operational needs into requirements, architectures, interfaces, and measurable acceptance criteria. They will develop autonomy capabilities, integrate algorithms and physical hardware, build production robotics software and simulation and validation workflows, and engineer dependable behavior under real operating conditions. The position involves designing experiments, diagnosing cross-disciplinary failures, and collaborating with mechanical, electrical, embedded, and AI engineers to deliver integrated hardware. Strong candidates demonstrate technical depth, sound judgment, and working systems. They should be able to explain a robot or subsystem they personally designed, implemented, and tested; the mathematical foundations and engineering tradeoffs involved; their contribution across algorithms, software, and hardware; how they diagnosed a difficult failure; measured performance results; and the conditions under which the system operated successfully.

Requirements

Degree in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, Aerospace Engineering, or a related discipline, or equivalent demonstrated experience.
Demonstrated ownership of a robotic or autonomous system tested on physical hardware.
Strong programming skills in C++ and Python, including debugging and profiling on Linux.
Strong foundations in linear algebra, coordinate transformations, probability, numerical methods, and rigid-body motion.
Deep expertise in at least one robotics area, with working knowledge of adjacent disciplines: estimation and localization; planning and controls; perception; or robotics systems.
Experience with ROS 2 or comparable robotics middleware, including communication, transforms, logging, and diagnostics.
Practical experience integrating and calibrating sensors such as cameras, IMUs, LiDAR, GNSS, encoders, or force sensors.
Ability to validate algorithms against physical measurements and explain discrepancies between simulation and real-world behavior.
Clear technical communication and ability to make progress through ambiguous engineering problems.

Nice To Haves

Experience with autonomous aircraft, mobile robots, manipulators, unmanned vehicles, or other complex electromechanical platforms.
End-to-end ownership of a subsystem from mathematical formulation through implementation and field validation.
Experience with real-time systems, embedded Linux, microcontrollers, motor controllers, or deterministic communication.
GPU programming, model optimization, or deploying perception models on constrained hardware.
Learning-based robotics, imitation learning, reinforcement learning, or vision-language-action models supported by physical deployment results.
Experience integrating AI models or LLM-based task planning with validated low-level controls and explicit execution constraints.
Experience with simulation tools such as Isaac Sim, MuJoCo, Gazebo, or equivalent environments.
Experience with system identification, actuator characterization, calibration optimization, or uncertainty analysis.
Field testing, reliability improvements, and transitioning research prototypes into repeatable deployments.
Peer-reviewed research, open-source contributions, robotics competitions, or independently built systems demonstrating exceptional technical execution.

Responsibilities

Own robotics development from concept through deployment.
Translate operational needs into system requirements, architectures, interfaces, and measurable acceptance criteria.
Develop and integrate autonomy algorithms for state estimation, localization, mapping, perception, motion planning, or control according to platform needs.
Integrate sensors, actuators, embedded computers, and communication interfaces into reliable robotic systems.
Develop modular, testable C++ and Python software with attention to timing, concurrency, resource constraints, and fault handling.
Create software-in-the-loop and hardware-in-the-loop workflows to evaluate behavior before and during physical testing.
Address sensor noise, calibration errors, communication delays, actuator limits, uncertain environments, and limited compute resources.
Instrument systems, collect data, establish performance baselines, and use results to guide improvements.
Trace problems through software, electronics, mechanics, and algorithms to identify root causes.
Implement health monitoring, operating limits, fault detection, and appropriate recovery or safe-state behavior.
Collaborate with mechanical, electrical, embedded, and AI engineers to resolve system tradeoffs and deliver integrated hardware.