Senior System Modeler: Physics‑Driven AI Compute

Unconventional AI; Palo Alto (CA); On-site; USD 170,000 - 260,000; Full time

Benefits offered by this job

Health benefits

401k matching

Unlimited PTO

Complimentary meals at Palo Alto офис

Job summary

Unconventional is seeking a Member of Technical Staff, System Modeling (Computation) in Palo Alto to build simulation frameworks for physics‑based computing systems powering ML workloads. You will work on extreme co‑design, bridging physics and ML, and contribute across multiple layers from algorithms to hardware.

Candidates have graduate degrees in AI/ML, CS, physics or related fields, experience with GPU‑accelerated ML simulations, and a track record delivering high‑performance numerical

Qualifications

• MS/PhD in a quantitative field or BS with substantial research depth.
• Scientific ML and numerical methods expertise.
• Deep expertise in numerical solvers (ODE, SDE, DDE) on parallel GPUs.
• Experience with high‑performance GPU kernel development and memory optimization.
• Experience building neural network surrogate models for complex dynamical systems.
• Solid understanding of modern AI/ML architectures and workflows.

Responsibilities

• Architect foundational solvers: large‑scale, GPU‑accelerated numerics and visualization tools.
• Bridge physics and ML: surrogate models and cross‑layer optimization via autodiff.
• Collaborate with hardware and algorithm teams to support simulation needs.

Skills

SciML & numerical methods

ML & systems fluency

PyTorch

GPU kernel development

Python engineering

Cross-layer optimization

Education

MS/PhD or BS with evidence

Tools

JAX

PyTorch

CUDA/Triton kernels

Job description

Unconventional is seeking a Member of Technical Staff, System Modeling (Computation) in Palo Alto to build simulation frameworks for physics‑based computing systems powering ML workloads. You will work on extreme co‑design, bridging physics and ML, and contribute across multiple layers from algorithms to hardware.

Candidates have graduate degrees in AI/ML, CS, physics or related fields, experience with GPU‑accelerated ML simulations, and a track record delivering high‑performance numerical