Feeny
Root Access

Machine Learning Engineer at Root Access (New York, NY)

Root Access· New York, NY·

Role details

Work type
Onsite
Employment
Full-Time

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).

Why work at Root Access

  • High-impact mission: Build the AI infrastructure that makes autonomous tractors, satellites, medical robots, and defense systems faster to develop and safer to certify.
  • Early-stage energy: Join as a founding engineer (Software Engineer, Machine Learning Engineer, Firmware/Embedded Engineer) with significant ownership and influence.
  • Top-tier backing: Backed by AlleyCorp and supported by accelerators like NVIDIA Inception and AWS Activate.
  • Culture: Flat structure; team of 8 with a strong technical bias (5 of 8 in engineering/technical roles); co-founders with deep industry knowledge (CEO Ryan Eppley built heavy machinery; CTO Samarpita Chowdhury has firmware expertise).
  • Location: Based in New York City; likely hybrid/office-first given hardware interaction needs; open roles listed as “New York City” on the careers page.
  • Perks: Competitive equity for early employees; hands-on work with cutting-edge AI models, embedded systems, and certification processes.

Application questions