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 coredesigning scalable, precision-focused systems running on
CPU and GPUand 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
Requirements
- 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
Benefits
We offer great career growth, ESOPs, Gratuity, PF and Health Insurance.
