System Modeling Engineer — Dynamic Systems Simulation

Unconventional AI; Palo Alto (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health benefits

401k matching

Unlimited PTO

Complimentary meals (Palo Alto office)

Job summary

Unconventional in Palo Alto is seeking a Member of Technical Staff, System Modeling (Dynamic Systems Simulation) to join a hands‑on R&D team building high‑fidelity behavioral simulators and PyTorch/JAX components that bridge physics and AI frameworks.

You will contribute to extreme co‑design, modeling analog/digital dynamics with neural approaches and integrate across hardware and software layers to accelerate next‑gen AI architectures, all within a collaborative, impact‑driven environment.

Qualifications

• MS/PhD in Electrical Engineering, Computer Engineering, or closely related fields (e.g., Applied Physics with a focus on solid‑state devices or VLSI), or BS with substantial evidence of equivalent research/engineering depth in circuit simulation.
• Knowledge of Analog and Mixed‑Signal circuit design: understand transistor level circuit 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 & Nonlinear Dynamics: grasp of state‑space representations and solving dx/dt = f(x, u, t) in ML context.
• Stochastic Processes & Noise: modeling and mitigating noise in real-world systems, including SDEs or Bayesian filtering.
• Modeling & Simulation: experience building high-fidelity circuit simulations with balanced performance and accuracy.

Responsibilities

• Develop high‑performance PyTorch or JAX components that model complex, time‑varying circuit‑based dynamic systems.
• Create and optimize simulation frameworks enabling rapid iteration across physics and AI layers.
• Contribute to cross‑layer system integration and ground models in physical reality.

Skills

Analog and Mixed-Signal circuit design

Advanced Neural Modeling (PyTorch or J

Education

MS/PhD in Electrical Engineering or related field

BS with substantial evidence of equivalent depth

Tools

PyTorch

JAX

CUDA

Triton

NumPy

Job description

Unconventional in Palo Alto is seeking a Member of Technical Staff, System Modeling (Dynamic Systems Simulation) to join a hands‑on R&D team building high‑fidelity behavioral simulators and PyTorch/JAX components that bridge physics and AI frameworks.

You will contribute to extreme co‑design, modeling analog/digital dynamics with neural approaches and integrate across hardware and software layers to accelerate next‑gen AI architectures, all within a collaborative, impact‑driven environment.