Robotics Jobs Colombia

Robotics Jobs Colombia on Rex.zone focuses on remote, full-time robotics engineering work that connects real-world robotic systems to modern AI/ML training workflows. These roles span robot perception, sensor fusion, mapping and localization, motion planning, autonomy validation, and simulation-to-real deployment, while also supporting data labeling, QA evaluation, and large language model evaluation for robotics copilots and planning assistants. You will collaborate with cross-functional teams to improve training data quality, annotation guidelines compliance, model performance improvement, and safe robot behavior using SLAM, ROS, computer vision, and automated test pipelines. Explore Rex.zone to apply, compare roles, and align your robotics career with production-grade autonomy systems and AI development.

Open Role: Robotics Engineer

About the Role

As a mid-senior Robotics Engineer, you will design, build, and validate autonomy capabilities for robotic platforms in a remote, full-time environment. Your work spans perception and planning pipelines, ROS-based integration, simulation workflows, and on-robot validation. You will also contribute to data-centric development by defining labeling specifications, reviewing annotation guidelines compliance, and running QA evaluation loops that increase training data quality and model performance improvement. Where applicable, you will partner with AI teams on prompt evaluation and large language model evaluation for robotics assistants that support planning, troubleshooting, and operator decision-making.

Responsibilities

Own robotics software components across perception, localization, mapping, planning, and control; build and maintain ROS/ROS2 nodes, message interfaces, and tooling for repeatable experiments; implement and tune SLAM and sensor fusion stacks for multi-sensor setups (camera, LiDAR, IMU, GPS); develop simulation-to-real validation, including scenario generation, regression tests, and autonomy KPI tracking; design data collection plans and curate datasets for computer vision annotation and sensor dataset labeling; define labeling instructions, sampling strategies, and acceptance criteria to improve training data quality; run QA evaluation of labeled data, identify systematic label errors, and drive corrective actions; collaborate on safety and reliability checks, including content safety labeling where human-robot interaction data is used; support LLM training pipelines for robotics copilots by providing evaluation sets and performing prompt evaluation and model output review when relevant.

Required Qualifications

Mid-senior experience delivering robotics or autonomy software into production or field testing; strong Python and C++ skills with debugging, profiling, and software quality practices; experience with ROS/ROS2, middleware, and distributed robotic systems; hands-on knowledge of SLAM, localization, mapping, and state estimation; experience with motion planning and trajectory optimization or sampling-based planning; familiarity with computer vision pipelines (calibration, detection, tracking) and sensor data handling; ability to design robust validation plans, interpret metrics, and improve model performance improvement through data and system changes.

Preferred Qualifications

Experience with autonomy evaluation frameworks, scenario-based testing, and large-scale simulation; familiarity with MLOps or data ops practices, including dataset versioning and annotation workflow management; exposure to data labeling and QA evaluation processes, including annotation guidelines compliance and review sampling; experience with reinforcement learning, imitation learning, or policy evaluation in robotics; understanding of LLM training pipelines, RLHF-style preference evaluation, or prompt evaluation in robotics support tools; domain experience in AMRs, drones, industrial robotics, or logistics automation.

Tools and Workflows

ROS/ROS2, Python, C++, Gazebo/Isaac Sim or comparable simulation tooling, CI/CD for robotics testing, scenario playback, telemetry analysis, dataset curation, and structured evaluation harnesses. Data-centric workflows may include computer vision annotation, named entity recognition for operator logs, content safety labeling for HRI data, and large language model evaluation for robotics copilots—applied with clear labeling instructions and measurable quality thresholds.

Compensation

Salary Range: 63360 to 126720 USD per year, depending on experience, role scope, and interview performance. Remote full-time role.

How to Apply on Rex.zone

Visit Rex.zone and search Robotics Jobs Colombia to find the Robotics Engineer listing, review the requirements, and submit your application. Keep your resume focused on ROS, SLAM, sensor fusion, planning, simulation testing, and measurable autonomy outcomes. If you have experience improving training data quality through data labeling, QA evaluation, prompt evaluation, or annotation guidelines compliance, highlight it clearly.

Frequently Asked Questions

Q: What does “Robotics Jobs Colombia” mean on Rex.zone if the country is listed as US?
It is an SEO-aligned jobs page targeting Robotics Jobs Colombia searches while keeping the role metadata defaults (Country: US) unchanged as requested. The role is explicitly marked Remote, so candidates can apply regardless of location constraints defined by the employer.
Q: Is this role fully remote and full-time?
Yes. The job metadata specifies Remote Type: Remote and Employment Type: FULL_TIME, and the role is designed for distributed engineering collaboration with remote validation and simulation-first workflows.
Q: What robotics domains are covered in this role?
Core areas include ROS integration, SLAM, sensor fusion, robot perception, motion planning, autonomy testing, simulation-to-real validation, and safety/reliability evaluation.
Q: How does this robotics role relate to AI/ML training workflows?
Robotics autonomy depends on data quality and evaluation loops. The role may include dataset curation, computer vision annotation, QA evaluation, annotation guidelines compliance, and creating evaluation sets that drive model performance improvement in perception and planning components.
Q: Do I need experience with RLHF or LLM evaluation to apply?
It is not required, but it is a plus. If the robotics stack includes an operator copilot or planning assistant, you may contribute to prompt evaluation and large language model evaluation, and provide feedback that improves reliability and safety.
Q: What skills should I emphasize for this posting?
Emphasize Robotics, ROS, SLAM, Sensor Fusion, Motion Planning, Computer Vision, Autonomy Testing, Simulation, Python, and C++. Add evidence of measurable autonomy improvements, robust testing, and data-centric iteration when applicable.

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