Robotics Jobs Cali

Robotics Jobs Cali is a remote, full-time job page on Rex.zone for engineers building real-world robotics systems end to end: perception (CV), localization and mapping (SLAM), motion planning, controls, and robot software (ROS/ROS2). These roles support production workflows across AI/ML model training pipelines, dataset creation, simulation, and on-robot validation—connecting robotics engineering with data labeling, QA evaluation, prompt evaluation for LLM copilots, and safety-critical testing. Explore roles with AI labs, tech startups, and robotics vendors while staying Remote in the US, with clear responsibilities, required skills, and how to apply through Rex.zone.

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Robotics Jobs Cali

LinkedIn Job Metadata: Title: Robotics Engineer | 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: Robotics, ROS2, Python, C++, SLAM, Computer Vision, Motion Planning, Control Systems, Gazebo, Isaac Sim, Sensor Fusion, Perception, Calibration, Path Planning, Embedded Systems, Linux, Git, CI/CD, Model Evaluation, Data Labeling, QA Evaluation, RLHF, Prompt Evaluation, Content Safety Labeling, Named Entity Recognition, LLM Training Pipelines, Training Data Quality, Annotation Guidelines Compliance, Model Performance Improvement | Salary Currency: USD | Salary Min: 63360 | Salary Max: 126720 | Pay Period: YEAR

About the Role

As a Robotics Engineer working remotely in the US, you will develop and validate robot autonomy features across perception, planning, and control. You will build ROS2 nodes and tooling, integrate sensors (camera, LiDAR, IMU), and run simulation-to-real workflows. The role connects classic robotics engineering with AI development practices: dataset curation, training data quality checks, annotation guidelines compliance, and model performance improvement through structured evaluation.

What You Will Do

You will design and implement robot software modules (ROS/ROS2), build perception pipelines (computer vision, sensor fusion), and support SLAM and localization. You will develop motion planning and control components, define test scenarios in simulation (Gazebo/Isaac Sim), and execute on-robot validation. You will collaborate on data labeling operations and QA evaluation for perception models, including error analysis, edge-case discovery, and content safety labeling for robot-facing vision/audio inputs where applicable.

Key Workflows You Will Support

You will contribute to end-to-end robotics development loops: collecting field logs, curating datasets, and improving training data quality; creating and enforcing annotation guidelines compliance for CV annotation and named entity recognition when robots interact with language interfaces; running large language model evaluation and prompt evaluation for robot copilots or operator-assist tools; and applying RLHF-style feedback where human ratings improve model behavior. You will help close the loop between model performance improvement and real-world robot metrics like collision rate, localization drift, and task success.

Required Qualifications

You have mid-senior experience delivering robotics features to real systems. You are proficient in Python and C++ and comfortable with Linux-based development. You have hands-on knowledge of ROS/ROS2, sensor integration, and debugging distributed robot software. You can reason about SLAM, calibration, coordinate frames, and motion planning fundamentals. You can design reliable tests, track regressions, and work with cross-functional teams spanning engineering, data operations, and evaluation.

Preferred Qualifications

Experience with simulation environments (Gazebo, Isaac Sim), hardware bring-up, and embedded constraints. Familiarity with CV annotation, computer vision datasets, and QA evaluation protocols. Exposure to LLM training pipelines, prompt evaluation, or RLHF processes for robotics assistants. Background in safety testing, content safety labeling, and structured evaluation for edge cases and failure modes.

Tools and Tech Stack

Common tools include ROS/ROS2, Python, C++, OpenCV, PCL, Linux, Docker, Git, CI/CD, and simulation frameworks (Gazebo, Isaac Sim). Data and evaluation tooling may include labeling platforms, dataset versioning, metrics dashboards, and evaluation harnesses for perception and large language model evaluation.

Compensation and Work Type

This is a Remote, FULL_TIME role in the US. Compensation range is USD 63360 to USD 126720 per YEAR, depending on scope, experience, and interview outcomes.

How to Apply on Rex.zone

Apply through Rex.zone with a resume highlighting shipped robotics systems, ROS/ROS2 modules, perception/planning/control contributions, and validation results. Include links to code samples, publications, demos, or technical writeups when available. Emphasize measurable outcomes such as reduced failure rates, improved localization accuracy, faster planning cycles, or higher task success rates.

Frequently Asked Questions

  • Q: What does “Robotics Jobs Cali” mean on Rex.zone if the role is Remote?

    It targets robotics job seekers searching for California-oriented robotics opportunities while keeping the position explicitly Remote in the US. Work is performed remotely, and collaboration is done through distributed engineering workflows.

  • Q: Is this strictly a robotics software role or does it include AI/ML work?

    It is primarily robotics engineering (ROS2, perception, SLAM, planning, controls) with strong integration into AI/ML workflows such as dataset curation, data labeling, QA evaluation, and model performance improvement through structured testing.

  • Q: Do I need experience with RLHF or LLM evaluation?

    Not required, but beneficial if you have experience with RLHF, prompt evaluation, or large language model evaluation—especially for robot copilots, operator assist tools, or language-enabled task interfaces.

  • Q: What types of annotation or evaluation might robotics engineers support?

    Common needs include computer vision annotation for perception (bounding boxes, segmentation, keypoints), training data quality audits, annotation guidelines compliance, and QA evaluation of model outputs. In language-enabled robotics, it can include named entity recognition, prompt evaluation, and content safety labeling.

  • Q: What experience level is this role?

    It is Mid-Senior level, focusing on engineers who can own modules end to end, ship reliable robotics features, and collaborate across engineering and data operations.

  • Q: Is the job full-time and remote?

    Yes. The job metadata specifies Employment Type: FULL_TIME and Remote Type: Remote, and those defaults remain unchanged.

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