About this opportunity
Root Access, Inc. lists this Machine Learning Engineer opportunity in new york, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
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).
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.