Job Title Robotics Software Engineer Experience 2-8 Years (Depending on the role and specialization)
Job Summary We are seeking a Robotics Software Engineer to design, develop, test, and deploy software for robotic systems. The ideal candidate will have experience in robotics programming, motion planning, sensor integration, computer vision, and real-time control systems. The role involves working closely with mechanical, electrical, AI, and embedded engineering teams to develop reliable and scalable robotic solutions.
Key Responsibilities - Design and develop software for robotic systems and autonomous platforms.
- Develop algorithms for robot perception, localization, mapping, and navigation.
- Integrate sensors such as LiDAR, cameras, IMUs, GPS, ultrasonic sensors, and encoders.
- Develop robot control software for motion planning and path optimization.
- Build and maintain software using the Robot Operating System (ROS/ROS2).
- Implement and optimize computer vision and AI-based robotic applications.
- Test, debug, and validate robotic systems in simulation and real-world environments.
- Collaborate with hardware engineers for actuator and sensor integration.
- Develop reusable software libraries and APIs.
- Create technical documentation and maintain code repositories.
- Troubleshoot field issues and improve system reliability.
Required Technical Skills Programming Languages - C++
- Python
- C
- MATLAB (preferred)
Robotics Frameworks - ROS (Robot Operating System)
- ROS2
- Gazebo
- MoveIt
- OpenCV
- TensorFlow or PyTorch (for AI-enabled robotics)
Robotics Concepts - Kinematics
- Dynamics
- Motion Planning
- Path Planning
- Robot Control Systems
- Localization
- SLAM (Simultaneous Localization and Mapping)
- Navigation Algorithms
Embedded Systems - Embedded Linux
- Real-Time Operating Systems (RTOS)
- Microcontrollers (STM32, Arduino, ESP32)
- CAN Bus
- UART
- SPI
- I2C
Sensors & Hardware - LiDAR
- RGB/RGB-D Cameras
- IMU
- GPS
- Ultrasonic Sensors
- Wheel Encoders
- Servo and Stepper Motors
Computer Vision & AI - Object Detection
- Image Processing
- Pose Estimation
- Machine Learning
- Deep Learning
- Sensor Fusion
Simulation Tools - Gazebo
- RViz
- Webots
- CoppeliaSim (V-REP)
- MATLAB/Simulink
Version Control & DevOps - Git
- GitHub
- GitLab
- Docker
- CI/CD Pipelines
Preferred Skills - Autonomous Mobile Robots (AMRs)
- Autonomous Guided Vehicles (AGVs)
- Industrial Robotics
- Drone Software Development
- Reinforcement Learning
- Edge AI
- NVIDIA Jetson
- NVIDIA Isaac SDK
- Cloud Robotics
- Linux system programming
Daily Responsibilities - Develop and test robotics software modules.
- Integrate and calibrate sensors.
- Debug robot navigation and localization issues.
- Optimize robot performance and safety.
- Run simulations before hardware deployment.
- Collaborate with multidisciplinary engineering teams.
- Participate in design reviews and sprint planning.
- Document software architecture and test results.
Soft Skills - Strong analytical and problem-solving skills
- Effective communication
- Team collaboration
- Innovation and creativity
- Attention to detail
- Adaptability
- Time management
- Continuous learning mindset
Education - Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, Mechatronics, or a related field.
Preferred Certifications - ROS Developer Certification
- NVIDIA Deep Learning Institute Certifications
- AWS Certified Machine Learning (preferred)
- Embedded Systems Certifications
- AI/ML Certifications
Tools & Technologies - ROS / ROS2
- Gazebo
- RViz
- MoveIt
- OpenCV
- Python
- C++
- Linux (Ubuntu)
- Docker
- Git
- MATLAB
- TensorFlow
- PyTorch
- NVIDIA Jetson
- Visual Studio Code
- CMake
KPIs - Software reliability and stability
- Robot navigation accuracy
- Localization and mapping performance
- Sensor integration success rate
- Defect density
- Test coverage
- Code quality and maintainability
- Deployment success rate
Typical Interview Topics - ROS architecture (nodes, topics, services, actions)
- Robot kinematics and dynamics
- SLAM algorithms
- Path planning (A*, Dijkstra, RRT)
- PID control and feedback systems
- Sensor fusion (Kalman Filter, Extended Kalman Filter)
- Computer vision using OpenCV
- C++ memory management
- Python for robotics
- Embedded Linux and RTOS concepts
- Motion planning with MoveIt
- Docker and CI/CD for robotics
- Real-time programming
- Autonomous navigation challenges
- Debugging robotic systems
