Applied AI Engineer: Physics-Based Modeling for Engineering

Acceler8 Talent; Cambridge (MA); Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Acceler8 Talent is partnering with an early-stage AI company in the United States that applies machine learning and physics-based modelling to tackle complex engineering challenges. They seek experienced Applied AI Engineers and Researchers who can fuse scientific computing with ML to build robust systems.

Location: Cambridge, MA, hybrid with three days on-site. The role offers opportunities at the AI-physics frontier, collaborating with researchers and engineers on real-world problems in

Qualifications

• 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.

Responsibilities

• Develop physics-based models for complex engineering systems.
• Combine traditional numerical solvers with machine learning models 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.

Skills

Physics-based modelling

Numerical simulation

Scientific computing

Applied machine learning

Tools

PyTorch

JAX

SciPy

Job description

Acceler8 Talent is partnering with an early-stage AI company in the United States that applies machine learning and physics-based modelling to tackle complex engineering challenges. They seek experienced Applied AI Engineers and Researchers who can fuse scientific computing with ML to build robust systems.

Location: Cambridge, MA, hybrid with three days on-site. The role offers opportunities at the AI-physics frontier, collaborating with researchers and engineers on real-world problems in