About the Role

We are seeking a Software Architect to lead the design and development of a next-generation dynamical simulation engine that combines high-performance numerical computation, control-theoretic modeling, and AI-driven predictive analytics.

You will architect and implement the computational core—designing scalable, precision-focused systems running on CPU and GPU—and integrate AI/ML modules for learning, estimation, and prediction. This is a hands-on, technically deep role with architectural ownership and cross-team leadership.

Key Responsibilities

Core Architecture & Simulation Engine

• Architect and implement a dynamical system simulation framework for complex, time-dependent physical and engineered processes.
• Develop and optimize numerical algorithms for multi-core CPUs and GPUs using C/C++, Python, and CUDA/OpenCL.
• Integrate control-theoretic models, including feedback systems, stability analysis, and perturbation analysis.
• Define simulation data structures, solver architectures, and modular interfaces for extensibility.

AI / Predictive Modeling Integration

• Collaborate with AI/ML teams to embed predictive models and data-driven controllers into the simulation loop.
• Architect efficient data exchange and compute workflows between numerical solvers and AI inference engines.
• Optimize hybrid AI + physics simulation performance.

Performance & Optimization

• Profile and tune performance-critical components for compute efficiency, memory management, and scalability.
• Develop benchmarking tools and regression frameworks for algorithm validation.

Leadership & Collaboration

• Lead a small team of simulation and algorithm engineers.
• Work closely with the Application Tech Lead and UI/backend teams for seamless integration.
• Establish architectural standards, review processes, and documentation practices.

• Bachelor’s or Master’s degree in Computer Science, Electrical/Mechanical Engineering, Control Systems, Applied Mathematics, or a related field.
• 10+ years of experience in high-performance computational software development.
• Deep understanding of:
• Control theory, dynamical systems, and feedback mechanisms
• Numerical methods, ODE/PDE solvers, and stability analysis
• Parallel and GPU computing (CUDA, OpenCL, OpenMP)
• C/C++, Python, and scientific computing libraries
• Proven experience integrating AI/ML frameworks (PyTorch, TensorFlow) with numerical systems.

Preferred Skills

• Experience building simulation engines from scratch, not just using existing platforms.
• Familiarity with distributed compute systems, profiling, and optimization tools.
• Exposure to DevOps for scientific codebases (CMake, CI/CD, Docker).

Soft Skills

• Strong analytical and problem-solving skills rooted in mathematical reasoning.
• Excellent communication and technical documentation abilities.
• Proven leadership and mentoring capability.

We offer great career growth, ESOPs, Gratuity, PF and Health Insurance.