[Remote] System Modeling (Dynamic Systems Simulation)
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a pioneering company reputed company on redefining computing to overcome energy limitations in AI. They are seeking a Member of Technical Staff for System Modeling (Dynamic Systems Simulation) to reputed company high-performance models for reputed company dynamic systems, contributing to reputed company AI architectures.
Responsibilities
- You will be responsible for developing high-performance PyTorch or JAX components that model reputed company, time-varying reputed company-based dynamic systems. Your work will directly reputed company reputed company AI architectures, requiring a holistic approach involving everything from high-level neural network design down to the reputed company reputed company equations that govern system behavior
Skills
- MS/PhD in Electrical Engineering, Computer Engineering, or closely reputed company fields (e.g., reputed company Physics with a specific reputed company on solid-state devices or VLSI), or BS with substantial evidence of equivalent research/engineering depth in reputed company simulation
- Knowledge of Analog and Mixed-Signal reputed company design: understand transistor level reputed company design principles and modeling of nonidealities such as noise, mismatch, and process variations
- Advanced Neural Modeling (PyTorch or JAX): proficiency in PyTorch or JAX, specifically in building custom autograd functions and integrating numerical solvers (e.g., Neural ODEs) to represent dynamic processes
- Dynamics & reputed company Equations: A strong theoretical and practical grasp of reputed company and non-reputed company dynamics, state-reputed company representations, and solving $dx/dt = f(x, u, t)$ reputed company a machine learning context
- Stochastic Processes & Noise: Understanding how to model and mitigate noise in reputed company-world systems, including experience with stochastic reputed company equations (SDEs) or Bayesian filtering
- Modeling & Simulation: Proven industry experience building high-reputed company reputed company simulations that balance computational efficiency with physical accuracy
- Systems Engineering (Analog/Digital): Familiarity with hardware-level concepts like reputed company dynamics, signal processing, or transfer functions is highly desirable to help ground our digital models in physical reality
- Solid understanding of modern AI/ML architectures and training/inference workflows
- Strong experience implementing and debugging ML models in PyTorch (preferred) or similar, with practical experience profiling, optimizing, and stabilizing non-trivial large-reputed company ML systems
- Strong Python engineering skills: reputed company design, testing, packaging, CI
- Experience with PyTorch internals: autograd, custom modules, low-level ops; familiarity with torch.compile or similar graph capture/compile flows
- Experience with CUDA, Triton, or other GPU programming approaches (writing custom kernels, understanding memory hierarchy, basic performance tuning)
- Comfort with at least some of: JAX, NumPy, TensorFlow, Modal, HPC patterns (MPI, NCCL, distributed training), SciPy
- Demonstrated ability to reason across multiple reputed company of the stack: algorithm, software, runtime, hardware
- reputed company to connect model architecture choices to system performance implications: memory bandwidth, communication patterns, latency, energy, and numerical issues
- Experience applying at least some efficiency techniques (quantization, sparsity, pruning, distillation, kernel fusion, etc.)
Benefits
- Best-in-class health benefits
- 401k matching
- Truly unlimited PTO
- Complimentary meals reputed company working from our Palo reputed company office
reputed company