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 ResponsibilitiesCore Architecture & Simulation Engine-
Architect and implement a dynamical system simulation framework for complex, time-dependent physical and engineered processes.
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Develop and optimize numerical algorithms for multi-core CPUs and GPUs using C/C++, Python, and CUDA/OpenCL.
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Integrate control-theoretic models, including feedback systems, stability analysis, and perturbation analysis.
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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.
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Architect efficient data exchange and compute workflows between numerical solvers and AI inference engines.
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Optimize hybrid AI + physics simulation performance.
Performance & Optimization-
Profile and tune performance-critical components for compute efficiency, memory management, and scalability.
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Develop benchmarking tools and regression frameworks for algorithm validation.
Leadership & Collaboration-
Lead a small team of simulation and algorithm engineers.
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Work closely with the Application Tech Lead and UI/backend teams for seamless integration.
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Establish architectural standards, review processes, and documentation practices.
Requirements
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Bachelor’s or Master’s degree in Computer Science, Electrical/Mechanical Engineering, Control Systems, Applied Mathematics, or a related field.
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10+ years of experience in high-performance computational software development.
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Deep understanding of:
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Control theory, dynamical systems, and feedback mechanisms
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Numerical methods, ODE/PDE solvers, and stability analysis
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Parallel and GPU computing (CUDA, OpenCL, OpenMP)
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C/C++, Python, and scientific computing libraries
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Proven experience integrating AI/ML frameworks (PyTorch, TensorFlow) with numerical systems.
Preferred Skills-
Experience building simulation engines from scratch, not just using existing platforms.
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Familiarity with distributed compute systems, profiling, and optimization tools.
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Exposure to DevOps for scientific codebases (CMake, CI/CD, Docker).
Soft Skills-
Strong analytical and problem-solving skills rooted in mathematical reasoning.
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Excellent communication and technical documentation abilities.
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Proven leadership and mentoring capability.
Benefits
We offer great career growth, ESOPs, Gratuity, PF and Health Insurance.
