Member of Technical Staff - Applied AI (AI)

Location: Cambridge, Massachusetts, United States; hybrid with 3 days onsite

Salary: $250,000–$400,000 per year; up to $230,000 base salary plus equity is also stated.

Company

Early-stage AI company applying machine learning and physics-based modelling to complex engineering challenges, with initial applications in AI data-centre infrastructure and engineering.

What you will do

• Develop physics-based models for complex engineering systems.
• Combine traditional numerical solvers with machine learning to improve simulation speed and accuracy.
• Build and validate scientific ML models against real-world measurements.
• Apply neural operators, surrogate modelling, and scientific computing techniques.
• Translate research into reliable tools and workflows used by engineering teams.

Requirements

• Strong background in physics-based modelling, numerical simulation, or scientific computing.
• Hands-on experience applying machine learning to real physical systems.
• Experience with PyTorch, JAX, or other scientific ML frameworks.
• Understanding of numerical methods, boundary conditions, and model validation.
• Ability to take research from experimentation through to practical deployment.

Culture & Benefits

• Work at the intersection of AI, physics, and engineering.
• Collaborate with researchers and engineers on challenging real-world problems.
• Develop technology for designing, simulating, and optimizing complex physical systems.
• Hybrid work with 3 days onsite in Cambridge, Massachusetts.
• Compensation includes salary and potential equity.

Hiring process

• Apply directly or contact the recruiter for a confidential discussion.