Software Architect
5 days ago
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.
- 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.
- 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.
- Profile and tune performance-critical components for compute efficiency, memory management, and scalability.
- Develop benchmarking tools and regression frameworks for algorithm validation.
- 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.
- 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).
- 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.
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