Junior System Modeling

Key Responsibilities

• Contribute to the implementation and optimization of GPU-accelerated simulators for ML on analog/unconventional hardware, focusing on specific modules and features within PyTorch.
• Assist in integrating physics-based device and system models into the PyTorch simulation environment to help expose early algorithm–hardware tradeoffs and enable cross-layer optimization.
• Support the maintenance and extension of the unified end-to-end simulation environment, helping to link theory, algorithms, and device models, and ensuring alignment between high-level and near-physical simulators.
• Implement and adhere to robust experiment tracking protocols to ensure simulation results, configurations, and non-idealities are reproducible and auditable.
• Collaborate with Algorithms and Hardware teams to gather requirements and ensure the modeling environment meets their needs for high-level algorithm development and lower-level hardware verification.

What We’re Looking For

• Strong Systems Foundation: A BS, MS, or PhD in Computer Science, Electrical Engineering, or a related technical field. Deep understanding of computer architecture and operating systems.
• Coding Proficiency: Strong skills in C++ and Python. Comfortable writing performance-critical code.
• AI/ML Exposure: Basic familiarity with the internals of deep learning frameworks (e.g., how a PyTorch graph is executed) and common model architectures.
• Mathematical Intuition: Solid grasp of linear algebra and calculus, essential for understanding both neural dynamics and hardware optimizations.
• First Principles Mindset: Enjoy digging into "why" things work and not afraid to challenge conventional software "best practices" to find a more efficient path.
• Bonus Points: Experience with compilers (LLVM, MLIR) or domain-specific languages like Triton. Exposure to GPU programming (CUDA) or other hardware accelerators. Prior research or internship experience in high-performance computing (HPC) or neuromorphic systems. Contributions to open-source AI or systems software projects.

Why Join Us?

• Mentorship: Learn directly from the architects who built the modern AI stack at companies like Intel, Databricks, and NVIDIA.
• Impact: Help build the machine itself, not just be a small cog in a giant machine.
• Unconventional Problems: Work on challenges that don't have a StackOverflow answer—you'll be defining the future of AI compute.
• Competitive Package: Significant equity and competitive salary at a well-funded, high-growth startup.