Robotics AI & Simulation Software Engineer

About the Role

Join us to develop the next generation of AI-enabled cleaning intelligence for autonomous robots operating in complex, dynamic, and human-populated environments.

This role sits at the intersection of robotics software engineering, applied AI, simulation, robot validation, perception model deployment, and safety-oriented system design. You will help build AI modules that make autonomous cleaning robots more intelligent, adaptive, robust, and certifiable in real-world outdoor operations.

You will work closely with robotics software, AI perception, navigation, mechatronics, and system engineering teams to translate advanced AI and simulation methods into reliable robot capabilities for real-world deployment.

Key Responsibilities

. Develop AI models, AI modules, and software features for cleaning intelligence, including debris detection, cleaning zone understanding, cleaning behavior adaptation, anomaly detection, environmental awareness, and future intelligent cleaning workflows.

. Design and implement AI-driven robotic behavior modules that interface with ROS 2, Nav2, mission planning, perception, localization, mapping, and robot application layers.

. Improve and maintain robot simulation environments using Gazebo, NVIDIA Isaac Sim, and related robotics simulation tools.

. Reduce the sim-to-real gap by improving robot models, sensor models, environment realism, scenario coverage, physics assumptions, perception inputs, and validation workflows.

. Develop simulation-based test suites for robot behavior, navigation, perception outputs, safety-related scenarios, and mission-level performance.

. Build automated regression tests to validate robot software behavior across releases, including scenario replay, simulation-based acceptance tests, edge-case testing, and performance benchmarking.

. Support AI perception development in areas such as model improvement, dataset preparation, model evaluation, deployment optimization, inference performance, and MLOps workflows.

. Work with the AI Perception Robotics Software Engineer to integrate perception model outputs into robot behaviors, cleaning intelligence features, safety layers, and mission-level decision-making.

. Develop tools and workflows for AI model lifecycle management, including data collection support, dataset versioning, model evaluation, benchmark reporting, deployment tracking, and field-performance feedback loops.

. Support development of safety-oriented software features such as speed-limiting logic, perception-based safety layers, warning/fallback behaviors, operational design domain checks, and safety-relevant robot state monitoring.

. Contribute to safety engineering activities, including risk analysis support, safety requirement tracking, validation planning, test evidence preparation, and technical discussions with safety certification agencies.

. Research and prototype future embodied AI capabilities for cleaning robotics, including vision-language models, vision-language-action models, world models, world-action models, and AI-based robot task reasoning.

. Validate AI and simulation features on real robots through field testing, data analysis, debugging, performance measurement, and iterative improvement.

. Contribute to scalable robotics software infrastructure, engineering practices, documentation, and release-quality validation processes.

Requirements

Education

. Bachelor's degree in Computer Science, Robotics, Computer Engineering, Electrical / Electronics Engineering, Mechanical Engineering, Mechatronics, or a related field.

. Master's or PhD is advantageous but not required.

Experience

. Experience developing robotics software for autonomous robots, mobile robots, intelligent machines, or related robotic systems.

. Experience with AI, computer vision, perception models, robot simulation, or autonomous system validation.

. Experience working with ROS 2-based robotic systems.

. Experience taking prototype software into real-world robot testing or deployment.

. Experience with simulation tools such as Gazebo, NVIDIA Isaac Sim, Webots, Unity, Unreal, or similar.

. Experience with applied AI development, model evaluation, model deployment, or AI software integration.

. Experience with safety-related robotics development, validation, or certification support is advantageous.

Technical Skills

. Strong C++ and Python programming skills.

. Experience with ROS 2, Linux-based development, and robotics middleware.

. Familiarity with Nav2, behavior trees, robot state machines, mission execution, or autonomous navigation systems.

. Hands-on experience with deep learning frameworks and deployment tools such as PyTorch, ONNX, TensorRT, CUDA, or similar.

. Good understanding of AI perception tasks such as object detection, semantic segmentation, scene understanding, tracking, or 3D perception.

. Experience building simulation scenarios, robot models, sensor models, test worlds, or automated simulation pipelines.

. Strong debugging, benchmarking, testing, optimization, and system integration skills.

. Ability to design structured validation tests for robot behavior, perception performance, simulation scenarios, and regression checks.

. Good understanding of how AI perception and robot intelligence interface with planning, control, navigation, safety, and mission-level behavior.

Nice to Have

. Experience with NVIDIA Jetson / AGX, CUDA, TensorRT, or GPU-accelerated AI deployment.

. Experience with NVIDIA Isaac Sim, Isaac ROS, synthetic data generation, domain randomization, or sim-to-real workflows.

. Experience with Gazebo simulation, ROS2 control, robot URDF/SDF models, plugins, and sensor simulation.

. Experience with MLOps, dataset management, model evaluation pipelines, experiment tracking, or scalable AI validation workflows.

. Experience with automated testing, CI/CD, simulation regression testing, scenario replay, or hardware-in-the-loop testing.

. Experience with safety standards or certification concepts such as ISO 13849, IEC 61508, ISO 3691-4, ISO 12100, functional safety, risk assessment, or safety validation.

. Experience with outdoor robotics, autonomous mobile robots, cleaning robots, service robots, autonomous vehicles, or field robotics.

. Interest in embodied AI, VLMs, VLAs, world models, robot foundation models, or AI-based task planning.

Why Join Us

. Work on real autonomous cleaning robots deployed in real-world environments.

. Build AI features that directly improve cleaning performance, safety, autonomy, and product intelligence.

. Develop simulation and validation infrastructure that improves robot reliability and release quality.

. Help shape the future cleaning intelligence stack for autonomous cleaning robots.

. Work across AI, robotics software, simulation, safety, perception, navigation, and field deployment.

. Contribute to future embodied AI capabilities for commercially meaningful robotics applications.