Applied Scientist: AI Physics & Simulation at Scale

Collinear AI; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Collinear.AI is seeking a Member of Technical Staff (Applied Scientist) with deep expertise in engineering sciences to work at the frontier of AI-accelerated simulation. You will collaborate with customers and internal research teams to build, test, and deploy AI Physics Models.

You will contribute across the full stack, curating high-fidelity simulation datasets, training physics-informed models, and delivering production-grade AI solutions to engineering teams, with domains including CFD,

Qualifications

• Ph.D. or Master’s degree in ML, Mechanical Eng., Electrical Eng., Computational Physics, Structural Mechanics, Semiconductor Eng., or related field.
• Strong grounding in deep learning with physics/engineering sciences.
• Experience implementing and training DL models.
• Clean Python code in Linux/HPC environments.
• Excellent written and verbal communication skills.
• Self-directed with autonomy in fast-paced sim+ML settings.

Responsibilities

• Design and orchestrate large-scale simulation campaigns using domain solvers (OpenFOAM, ANSYS, COMSOL, Abaqus).
• Train AI models on physics datasets and rigorously evaluate coverage, accuracy, and output quality.
• Build robust automated frameworks for dataset creation, simulation pipelines, and model evaluation.
• Architect agentic workflows and RAG systems connecting LLMs with engineering pipelines.
• Collaborate with research to analyze training runs and diagnose bottlenecks.
• Lead research initiatives and manage technical communications with external teams.

Skills

Deep learning

Physics foundation

Python programming

HPC environments

Communication skills

Autonomy

Education

Ph.D. or Master’s in ML/Engineering

Tools

OpenFOAM

ANSYS

COMSOL

Abaqus

Job description

Collinear.AI is seeking a Member of Technical Staff (Applied Scientist) with deep expertise in engineering sciences to work at the frontier of AI-accelerated simulation. You will collaborate with customers and internal research teams to build, test, and deploy AI Physics Models.

You will contribute across the full stack, curating high-fidelity simulation datasets, training physics-informed models, and delivering production-grade AI solutions to engineering teams, with domains including CFD,