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This job expired on 06/09/2026. It no longer accepts applications.
Lead Robotics Engineer (Modelling & Simulation)
SoftServe
Job description
About the role
SoftServe is seeking a Lead Robotics Engineer to design and deliver advanced robotics, physical AI, and multi‑fleet management solutions that bridge simulation and real‑world industrial environments. You will work on intelligent capabilities for outdoor vehicles, digital twins, and autonomous systems to drive innovation and operational efficiency.
Key responsibilities
- Design and develop robotics and industrial software solutions using digital twins and physical hardware to enable intelligent automation.
- Lead process modeling and optimization for continuous, discrete, and event‑driven systems across industrial settings.
- Develop prototypes and production‑ready robotics solutions in collaboration with cross‑functional teams.
- Integrate AI‑driven capabilities into existing equipment to enhance functionality and performance.
- Oversee testing, validation, and deployment in both simulated and real‑world environments.
- Define and implement automated robotic systems that improve production efficiency and precision.
- Provide expertise in control systems, motion planning, sensing, and decision‑making.
- Mentor engineers, conduct technical reviews, and influence architectural decisions.
Required profile
- 5+ years of software development experience with C++, Python, or Julia, including real‑time and system programming.
- Proven track record designing and implementing robotics or industrial automation solutions.
- Strong knowledge of continuous, discrete, and event‑driven system modeling methodologies.
- Experience with distributed control systems and Unix/Linux environments.
- Demonstrated ability to lead technical initiatives and mentor engineering teams.
Required skills
- C++
- Python
- Julia
- MATLAB / Simulink
- Mathematica
- Modelica
- Ansys
- OpenFOAM
- Gazebo
- NVIDIA Isaac
- V‑REP
- Control theory, estimation, optimization
- Robotics algorithms for linear and nonlinear systems
- Distributed control systems
- Unix/Linux
- CI/CD pipelines
- System monitoring tools
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