Robotics Jobs Monterrey is a dedicated Rex.zone listing for mid-senior, full-time remote robotics engineers supporting modern AI/ML-enabled robotics workflows. This job family covers robot software development, perception, control, and autonomy—spanning ROS/ROS2, sensor fusion, motion planning, and simulation-to-real validation. You will build and evaluate robot behaviors using structured testing, QA evaluation, and data-driven iteration, improving model performance and system reliability. Whether your background is computer vision, SLAM, reinforcement learning, embedded systems, or safety engineering, this page helps you find and apply to remote roles with AI labs, tech startups, and robotics teams scaling production deployments.
Title: Robotics Engineer (Remote) Date: 25-02-2026 Company: Rexzone Country: US Remote Type: Remote Employment Type: FULL_TIME Experience Level: Mid-Senior Industry: Technology Job Function: Engineering Skills: ROS2, C++, Python, Motion Planning, SLAM, Sensor Fusion, Computer Vision, Control Systems, Gazebo, Linux Salary Currency: USD Salary Min: 63360 Salary Max: 126720 Pay Period: YEAR
As a Robotics Engineer working remotely through Rex.zone, you will design, implement, and validate robot autonomy features across perception, planning, and control. You will translate product requirements into reliable robot behaviors, integrate sensors (camera, LiDAR, IMU), and improve navigation and manipulation pipelines. The role emphasizes training data quality and evaluation discipline: you will define test protocols, investigate failure modes, and iterate on algorithms to drive model performance improvement and field reliability. You may collaborate with AI/ML teams on reinforcement learning, imitation learning, and LLM-assisted tooling, while maintaining strong software engineering practices for production robotics.
You will own end-to-end robotics engineering tasks including ROS2 node development, perception integration, motion planning, and control tuning. You will build repeatable evaluation workflows, including simulation regression tests and real-world QA evaluation, to measure autonomy performance. You will conduct data labeling coordination for robot perception datasets when needed, define annotation guidelines compliance for vision tasks, and partner with ML engineers to improve models. You will debug complex multi-sensor issues, improve latency and reliability, and document system architecture, interfaces, and operational playbooks for deployment and support.
Common workflows include ROS2 orchestration, bag recording/replay, sensor calibration, state estimation, SLAM tuning, and motion planning validation in simulation and on hardware. You will use Python and C++ for robotics code, Linux for systems engineering, and tools like Gazebo/Ignition, RViz, and CI pipelines for regression testing. For AI/ML-adjacent tasks, you may support computer vision annotation, named entity recognition for robotics logs/alerts, prompt evaluation for operator tooling, and content safety labeling for human-robot interaction datasets where applicable.
Mid-senior experience building robotics systems in production or advanced R&D settings. Strong C++ and Python skills with Linux proficiency. Hands-on experience with ROS/ROS2, sensor fusion, SLAM, motion planning, and control systems. Ability to design measurable evaluation metrics, perform systematic debugging, and maintain high engineering quality through reviews, tests, and documentation. Experience collaborating cross-functionally with hardware, QA, and AI/ML stakeholders.
Experience with computer vision and deep learning for perception, including dataset design and training pipeline integration. Familiarity with reinforcement learning from human feedback (RLHF) concepts for policy refinement, imitation learning, or human-in-the-loop evaluation. Experience with simulation-to-real transfer, safety constraints, and operational monitoring. Knowledge of robotics QA evaluation frameworks, test automation, and incident triage in deployed fleets.
Rex.zone connects candidates to remote, full-time robotics roles aligned with real-world AI/ML and robotics production needs. You will find opportunities spanning AI labs, tech startups, and robotics teams that value structured evaluation, training data quality, and measurable autonomy improvements. Use this page to explore Robotics Jobs Monterrey listings, compare role requirements, and apply efficiently through a job page optimized for discoverability and recruiter workflows.
Apply via Rex.zone with a resume highlighting robotics projects, ROS2 experience, perception/planning/control contributions, and measurable outcomes (latency reduction, success rate improvements, autonomy KPIs). Include links to code repositories, publications, demos, or simulation videos where available. Emphasize evaluation rigor, QA practices, and any experience with dataset creation, data labeling, or ML model validation in robotics contexts.
Yes. The role on this page is explicitly marked Remote and is designed for distributed collaboration with robotics and AI/ML teams.
Yes. Employment Type is FULL_TIME with an annual salary range listed in USD.
Mid-Senior candidates are targeted, with expectations of owning autonomy components, evaluation workflows, and production-quality engineering practices.
Typical domains include ROS2 development, perception (computer vision), sensor fusion, SLAM, motion planning, control systems, and simulation-based validation.
Modern robotics pipelines often use ML-based perception and policy learning. You may work with training data quality, evaluation metrics, QA evaluation, and human-in-the-loop iterations that improve model performance and autonomy reliability.
It is helpful. Robotics teams frequently rely on labeled perception datasets and structured evaluation; familiarity with annotation guidelines compliance and dataset QA can strengthen your application.
Common employers include technology companies such as AI labs, tech startups, robotics product companies, and teams that integrate robotics into real-world operations.
Apply through Rex.zone using the job listing and include relevant robotics engineering evidence such as project outcomes, code samples, demos, or publications.
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