4 часа назад
AI Engineer (Physics Simulation)
190 000 - 260 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Engineer (Physics Simulation): Developing and scaling operator intelligence infrastructure for hardware design with an accent on transient domain modeling and physics-informed machine learning. Focus on integrating temporal propagation schemas, optimizing simulation throughput, and hardening production-grade AI models for Tier-1 semiconductor customers.
Location: Palo Alto, CA (Hybrid)
Compensation: $190,000 – $260,000 + Equity
Company
is an early-stage startup building operator intelligence infrastructure that accelerates hardware design validation using foundation models trained on structured physics data.
What you will do
- Leverage the framework to develop novel applications for transient domain modeling, interactions, and dynamics.
- Experiment with temporal propagation schemas using both classical and learned approaches.
- Generate and curate training and verification samples using existing data infrastructure.
- Iterate on prototypes and harden features in collaboration with customers.
- Work cross-functionally with physicists, AI researchers, and computational geometry experts to deploy production-ready systems.
Requirements
- MS/MSc with 4+ years of experience or PhD with 2+ years of experience.
- 2+ years of experience building or using physics simulators (FEM, FEA, Molecular Dynamics, FDTD).
- Applied machine learning experience (Computer Vision, GraphNN, Transformer Architectures).
- Proficiency with PyTorch, Numpy, and Cuda.
- Experience contributing to production data processing systems and software design standards.
- Strong discipline in CI, regression testing, and validation.
Nice to have
- Experience applying ML to meshing geometry or accelerating FEM/DFT simulations.
- Background in moving early-stage prototypes to production environments at a startup or national lab.
- Experience leveraging simulation for design or data generation.
Culture & Benefits
- Opportunity to define a foundational abstraction layer in an early-stage, high-impact startup.
- Work directly with technical leadership including the CTO and CEO.
- Collaborative, small, and friendly team environment.
- Greenfield opportunities to architect large parts of the core system.
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