Robotics Architect (Modelling & Simulation)
SoftServe · Remote - USA · Full-time · 2026-08-31
Job description
ABOUT THE ROLE
In this role, you will work at the intersection of robotics, AI, and real-world hardware – building physical AI and multi-fleet management systems for outdoor vehicles in collaboration with a globally recognized industry leader. You will go beyond simulation into practical application, both developing new capabilities and retrofitting existing equipment with intelligent components.
RESPONSIBILITIES
- Design and develop solutions for diverse robotics and industrial systems, working with digital twins of real-world hardware
- Lead process modeling and optimization for continuous, discrete, and event-driven systems
- Build rapid prototypes and production-ready solutions for robotics and industrial applications
- Collaborate with cross-functional teams to retrofit existing equipment with intelligent, AI-driven components
- Test robotics and industrial solutions in both simulation and real-world environments
- Design automated robotic systems that enhance production efficiency and precision within target industries
- Research emerging trends in robotics – control, motion planning, sensing, and decision-making – and apply findings to active engagements
REQUIREMENTS
- 6+ years of software development experience in C++, Python, or Julia, including system programming and real-time systems
- Proven experience modeling continuous, discrete, and event-driven systems
- Strong command of simulation frameworks such as MATLAB/Simulink, Mathematica, Modelica, Ansys, or OpenFOAM
- Hands-on experience with physics-based simulation tools, including Gazebo, NVIDIA Isaac, or V-REP
- Solid understanding of control theory, estimation, and optimization techniques for linear and nonlinear systems
- Proven ability to design and implement complex, efficient algorithms for robotics systems
- Experience with distributed control systems and Unix/Linux environments
- Familiarity with testing practices, CI/CD pipelines, and monitoring for complex systems