Modelling Engineer

We are looking for hardware modeling engineers to build functional and performance models for a next-generation optical computing platform. In this role, you’ll work closely with experienced modeling engineers to develop models for novel compute blocks such as optical GEMM engines, SRAM-based vector processors, and advanced dataflow architectures.

This position is well suited for recent graduates with strong academic experience, as well as engineers with 3+ years of industry experience who are interested in transitioning into hardware modeling for cutting-edge AI accelerators.

• Develop functional and performance models of hardware compute blocks
• Implement simulation components within the Yin Yang (libyy) event-driven framework
• Write clean, modular, and maintainable C++ code for hardware simulation
• Integrate models with RTL simulation and validation workflows
• Create test cases and validate model correctness
• Contribute to trace generation and analysis infrastructure
• Collaborate with senior engineers on modeling methodologies and best practices
• Debug and optimize simulation performance
• Document models, interfaces, and assumptions for team use

• Bachelor’s degree in Electrical Engineering, Computer Engineering, or Computer Science (MS or PhD preferred)
• 3+ years of software development experience (exceptional new graduates with strong academic projects will be considered)
• Strong proficiency in C++ or C
• Solid understanding of computer architecture fundamentals (pipelines, memory hierarchy, basic processor concepts)
• Coursework or project experience in computer architecture, digital design, or hardware systems
• Ability to read and interpret technical specifications
• Strong problem-solving and debugging skills
• Effective communication and collaboration skills
• Experience with Python scripting

• Experience with hardware simulation, modeling, or verification
• Familiarity with System
  
  C, Verilator, or hardware description languages
• Background in performance-critical software development
• Understanding of event-driven programming or simulation frameworks
• Exposure to computer architecture research or academic projects
• Knowledge of machine learning workloads and neural network operations
• Experience with Git, Linux-based development environments, and build systems