Who we are:

Our name is inspired by Theodore Roosevelt’s ‘Citizenship in a Republic’ speech, which pays homage to the ‘(hu)man in the Arena’. To us, entering the Arena means committing oneself fully and accepting the risk of failure in the pursuit of an audacious, worthy cause.

We’re a close-knit team of scientists and builders redefining the future of hardware engineering. If you share our passion for delving deep into real-world problems and solving them with fully autonomous AI, join us in the Arena.

What we do:

Our collective future is being built in the physical world, but the builders of tomorrow’s technology can no longer rely on yesterday’s tools. At Arena, we’re building the world’s first AI industrial engineer designed to solve the most complex hardware and manufacturing challenges. Our product, Atlas, is built with an understanding of the behavior of physical systems, powered by a superior knowledge of core domains of physics. Paired with its ability to reason about multimodal industrial data, Atlas can test, debug, optimize, and repair physical systems and products in the real world. Arena is already trusted by some of the most advanced industrial companies in the world (AMD, Bausch & Lomb), and we're rapidly already scaling into the defense, automotive, and aerospace industries, and we’re just getting started.

About the role:

As a Principal Research Scientist, Electromagnetism, you will lead the architecture, training, and validation of our electromagnetic foundation model, bridging numerically solved physics equations, neural operators, and product-grade simulation.

How you will contribute:

• Model Architecture Research
  • Design FNO/AFNO/Deformation-FNO/U-FNO multiscale operator architectures with embedded physical constraints
  • Implement causality/passivity enforcement and uncertainty calibration
• Proprietary Training Data Corpora
  • Specify coverage targets
  • Work with Arena’s Platform Engineering team to orchestrate solver farms and synthetic generation
  • Work with Arena Electrical Engineers to define a set of requirements and interface for physically-generated training data via hardware-in-the-loop test campaigns
  • Develop sim-to-real calibration using for example VNA/near-field/BER measurements
• Evaluation & Validation
  • Build automated accuracy and constraint eval suite
  • Own releases and reporting
• Optimization & Performance
  • Profile inference latency and throughput
• Leadership & Documentation
  • Author design docs, experiments, and technical reports

You have:

• PhD or equivalent research track in Electrical Engineering, Applied Physics, Computer Science, or Applied Math
• Proven expertise building and training large foundation models
• Experience with FNO and/or Neural Operators
• Understanding of EM solvers (FEM/FDTD/MoM)
• Strong Python, PyTorch/JAX, C/C++ for bindings
• Proven record of physics-constrained ML or scientific simulation deployment
• [Preferred] Prior work on passivity/causality enforcement in learned models
• [Preferred] Familiar with PDN, high-speed channel design, and EMI compliance testing
• [Preferred] Experience and familiarity with high performance principles (e.g. Slurm for scheduling, message passing workloads, etc.), and cloud service provider HPC ecosystems (e.g. AWS Batch, Elastic Fabric Adapter, etc.)

Benefits & Perks Include:

• 100% of the monthly premium for Aetna medical insurance, plus vision and dental coverage
• 401(k) Retirement Plan
• Unlimited PTO
• Lunch every day from local restaurants via Sharebite
• Relocation support provided (NYC or SF)

The base salary range for this position is $250,000 - $350,000 yr. However, base pay offered may vary depending on job-related knowledge, skills, and experience. In addition to base salary, we also offer competitive equity and benefits packages.