Robotics Solution Engineer Job in Cynlr - Cybernetics H.i.v.e

Job Title: Robotics Solution Engineer

Location: Bengaluru

Key Focus Areas:

The ideal candidate will have experience and expertise in 40-60% of the following domains:

• Task Development: Breaking down complex robotic tasks (e.g., pick, orient, place) and designing efficient workflows.
• Simulation and Validation: Using advanced physics-based simulation tools to model and validate robotic systems and interactions.
• System Integration: Seamless integration of hardware, software, and sensors tailored to customer environments.
• Customer-Centric Solutions: Customizing robotic solutions to fit specific customer requirements and constraints.
• Foundational R&D and ML Development: Supporting research and machine learning algorithm development to enhance robotic perception, autonomy, and decision-making.

Roles and Responsibilities:

Physics-Based Simulation Development:

• Develop comprehensive physics-based models for robots, environments, and their interactions.
• Create and validate dynamic models involving rigid body dynamics, contact physics, material properties, and compliance, especially for multi-arm robotic systems.
• Build and maintain digital twins of physical robots and real-world environments.

Algorithm Development & Implementation:

• Design, implement, and validate control and motion planning algorithms for multi-arm robots, focusing on manipulation and grasping.
• Optimize kinematics, dynamics, and force-based control strategies for real-time robotic applications.
• Support learning-based algorithm implementation for real-time perception and manipulation, including simulation-based testing and validation.

Machine Learning Applications:

• Apply machine learning techniques to robotic perception and decision-making.
• Implement learning-based algorithms for perception and manipulation tasks.

Testing, Validation & Optimization:

• Develop protocols to validate simulation accuracy by bridging virtual and real-world performance.
• Create automated test sequences and metrics for robust validation across various scenarios.
• Analyze simulation results to enhance system performance, safety, and reliability, suggesting design improvements.

Collaboration & Cross-Functional Support:

• Work closely with controls engineers to validate and tune control systems in simulation.
• Collaborate with algorithm, software, and hardware teams to refine systems and resolve issues.
• Provide insights from simulation analyses to guide product improvements.

Documentation & Reporting:

• Document simulation approaches, assumptions, and validation outcomes clearly.
• Prepare detailed reports on system performance, testing results, and optimization opportunities.

Skills and Experience:

Core Expertise:

• Advanced physics-based modeling and numerical simulation techniques.
• Deep understanding of robot kinematics, dynamics, and control theory.
• Experience with simulation validation and verification methodologies.
• Sensor modeling for cameras, force/torque sensors, etc.
• Motion planning algorithm knowledge.
• Familiarity with machine learning frameworks (PyTorch, TensorFlow) and real-time control implementation.

Software & Tools:

• Experience with physics simulation platforms like NVIDIA Isaac Sim/Omniverse, CoppeliaSim, Mujoco, PyBullet, PhysX, Gazebo, or equivalents.
• Proficient in Python and C++ for scripting and automation tasks.
• Comfortable integrating CAD software and managing version control with Git.

Engineering & Analysis:

• Skills in system dynamics modeling and error analysis.
• Developing test plans and performing root cause analysis.
• Conducting feasibility studies and model validation.

Required Qualifications:

• Bachelor s or Master s degree in Robotics, Mechanical Engineering, or related fields.
• Minimum 3 years of professional experience in robotics engineering, with a focus on simulation and modeling.
• Strong foundation in robot kinematics, dynamics, and control systems.
• Proficient in Python and C++ programming.
• Experience with physics engines (PhysX, Bullet, PyBullet) and validating simulation results with real-world data.

Preferred Qualifications:

• Master s or PhD in Robotics, Computer Science, or a related discipline.
• Hands-on experience with NVIDIA Isaac Sim/Omniverse or similar simulation platforms.
• Background in computer graphics, sensor modeling, and digital twin technologies.