Research Engineer: AI/ML enhanced control engineering

Analyze, model, and simulate dynamic and uncertain systems using AI, control theory, and computer science methods.

Develop and apply data-based improvements to model-based control concepts for constrained linear, nonlinear, and distributed systems with uncertainties.

Collaborate closely with customers to prepare solution approaches and minimum viable software products tailored to product-specific requirements.

Educational Qualification: MS/MTech or PhD from top Indian or international institutes in relevant engineering or computer science fields.

Work Experience Required: Minimum 3 years.

Strong knowledge of modern control theory, including Lyapunov stability, optimal control (LQR/LQG), adaptive and robust control.

Proficiency in AI/ML methods (deep learning, GPRs, bagging/boosting, surrogate modeling, reduced order models), Python programming, MATLAB, Simulink, and theory of ODEs with numerical solution methods.

Experienced in integrating AI/ML techniques with control engineering in complex and uncertain dynamic systems.

Capable of system-level thinking for holistic problem-solving and pattern recognition in dynamic environments.

Demonstrates ability to transfer academic and industrial research into practical software solutions for industrial products.