Physics ML Engineer: Foundation Models & Real-Time GPUs

5V Tech

New York (NY)

On-site

USD 140,000 - 210,000

Full time

8 days ago

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Job summary

5V Tech in New York City seeks a Machine Learning Engineer to develop physics foundation models and their infrastructure. You will tackle deep learning, scientific computing, geometry, and physics, turning research ideas into working systems with focus on speed and reliability.

You will collaborate with engineers across software, electrical, firmware, and ML disciplines to push real‑time performance and scalable training pipelines on GPU clusters using PINNs, FNOs, and related architectures.

Qualifications

Master's or PhD in CS, Math, EE, Physics with ML focus.
4+ years of expert PyTorch or JAX experience.
Hands-on experience with PINNs or FNOs.
Strong knowledge of PDEs, vector calculus, and automatic differentiation.
Proficiency with NumPy/SciPy and Python.

Responsibilities

Design and train deep learning models for physics foundation model applications.
Develop high-performance data pipelines for geometric and engineering data.
Work with complex engineering formats including ODB++, IPC-2581, STEP, Gerber.
Collaborate on connecting upstream Graph Neural Networks or LLMs mapping schematics to spatial engines.
Develop representations and processing pipelines for complex spatial and geometric datasets.
Build and optimise training and inference pipelines on GPU clusters.
Experiment with Scientific ML approaches including PINNs, FNOs, and related architectures.
Collaborate with software, electrical, firmware, and ML engineers throughout development.