Robotics Engineer

Analog; Abu Dhabi; On-site; AED 180,000 - 300,000; Full time

Job summary

Analog is seeking a Robotics Engineer to design, develop, and test intelligent robotic systems for real-world deployment. You will lead perception, estimation, and control work across embedded and edge devices, collaborating with researchers, engineers, and product teams.

Ideal candidates have 2+ years in robotics, strong C++/Python skills, and hands-on ROS/ROS2 experience, plus familiarity with LiDAR-based perception and cloud robotics platforms.

Qualifications

• 2+ years of robotics engineering experience.
• Strong proficiency in C++ and Python for robotics/AI development.
• Experience with ROS/ROS2 and LiDAR-based perception.

Responsibilities

• Develop and integrate perception systems using computer vision, AI, and sensors.
• Design state estimation and sensor fusion pipelines (SLAM, EKF/UKF).
• Create control and planning algorithms from PID to MPC.
• Integrate modules into robotic systems with real-time performance.
• Collaborate with cross-functional teams to advance robotics projects.

Skills

C++

Python

ROS/ROS2

Tools

ROS/ROS2

Gazebo

Isaac Sim

Webots

Git

CI/CD

Docker

RViz

Job description

Robotics Engineer

As a skilled Robotics Engineer to join our advanced robotics team. In this role, you will design, develop, and test intelligent robotic systems that leverage AI, computer vision, perception, estimation, sensor fusion, and control algorithms. You will collaborate with a multidisciplinary team of researchers, engineers, and product developers to bring robotic capabilities from concept to deployment in real world environments.

Responsibilities

AI & Perception

• Develop and integrate perception systems using computer vision, deep learning, and multimodal sensing.
• Build robust pipelines for real time detection, recognition, tracking, and scene understanding.
• Implement frameworks for training, testing, and deploying AI models on embedded and edge devices.

Estimation & Sensor Fusion

• Design algorithms for state estimation, localization, and mapping (e.g., SLAM, visual inertial odometry).
• Build and maintain sensor fusion pipelines combining LiDAR, cameras, IMU, radar, and GNSS.
• Implement probabilistic filters (Kalman, EKF/UKF, Particle) for robust estimation under uncertainty.
• Support robustness through time synchronization, calibration, and sensor noise management.

Controls & Planning

• Develop and implement control strategies from PID and adaptive controllers to Model Predictive Control (MPC).
• Create trajectory tracking and motion planning algorithms that handle noisy inputs and dynamic environments.
• Support research into robust target tracking and disturbance rejection.
• Help optimize control architectures for stability, safety, and performance in both simulation and real world testing.

System Integration & Deployment

• Integrate estimation, perception, and control modules into robotic systems, ensuring seamless hardware and software interoperability.
• Conduct simulations, validation, and field tests to evaluate performance.
• Optimize algorithms for real time execution on CPUs, GPUs, and FPGAs.

Collaboration & Growth

• Work closely with senior engineers and technical leads to solve complex robotics challenges.
• Collaborate with multidisciplinary teams in hardware, embedded systems, and software.
• Stay current with advances in robotics, AI, perception, estimation, and controls, and bring new ideas into applied solutions.

Qualifications

• 2+ Experience in robotics engineering, with strong proficiency in C++ and Python for robotics and AI development.
• Hands on experience with robotics frameworks such as ROS or ROS2.
• Working knowledge of SLAM and LiDAR based perception systems.
• Exposure to reinforcement learning algorithms in simulation or on real robots.
• Familiarity with cloud based robotics platforms (e.g., AWS RoboMaker, Azure IoT Hub, Google Cloud Robotics).
• Proficiency with simulation tools (e.g., Gazebo, Isaac Sim, or Webots) and visualization frameworks (e.g., RViz).
• Strong software engineering practices: version control (Git), CI/CD, containerization (Docker).