layiq
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Job opportunity
Machine Learning Engineer
Root Access
New York City, New York, United States
Source: Root Access careers · View original posting
Employer job description
From Root Access's posting. “We” and “our” refer to the employer.
About the company
Root Access is a frontier electronics company. We are a NYC-based startup funded by top investors. Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning.
Core Responsibilities
Architect Physics Foundation Models:
Design and train deep learning models.
Build the ECAD Data Pipeline:
Develop high-performance asset pipelines to convert geometric, discrete, and multi-layer PCB files (ODB++, IPC-2581, STEP, Gerber) into continuous space data.
Multi-Modal Architecture Integration:
Collaborate on connecting upstream Graph Neural Networks (GNNs) or LLMs mapping schematic topologies to downstream spatial physics engines.
Optimize for Real-Time Execution:
Optimize training and inference pipelines on GPU clusters.
Required Technical Skills & Qualifications
Education:
Master’s or Ph.D. in Computer Science, Mathematics, EE, Physics, or a related quantitative field with a focus on Scientific Machine Learning (SciML).
Deep Learning Frameworks:
4+ years of expert-level experience with PyTorch or JAX.
SciML Expertise:
Direct, hands-on experience building and training PINNs, FNOs, etc.
Mathematical Depth:
Exceptional understanding of partial differential equations (PDEs), vector calculus, automatic differentiation (autograd), and numerical optimization algorithms (Adam, L-BFGS).
Data Pipelines:
Strong proficiency in manipulating spatial or geometric datasets using Python libraries (
NumPy, SciPy, Shapely, Open3D
, or custom voxelization matrices).