Physics Informed Neural Networks Engineer Jobs

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Today

Machine Learning Engineer

Optimal Inc. Warren, MI

Warren, MI

Today

Full time Ai Ml Artificial Intelligence Data Science

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Job Description

Optimal Inc. is seeking a Machine Learning Research Scientist in Warren, MI to design and deploy AI models that merge physical principles with multimodal data. The role emphasizes Physics-Informed Neural Networks (PINNs) and predictive world models for simulating complex systems and forecasting real-world behavior.

Focus Areas

Physics-Informed Neural Networks (PINNs)
Predictive world models for learning system dynamics
Physics-informed machine learning approaches for simulation and forecasting

Responsibilities

Develop and implement Physics-Informed Neural Networks (PINNs) and other physics-informed machine learning models.
Build multimodal models that integrate inputs such as images, sensor measurements, time-series, and simulation outputs.
Create predictive world models to learn system dynamics, simulate environments, and forecast future states.
Integrate physics-based simulations with data-driven machine learning methods.
Validate accuracy, physical consistency, and performance using real-world or simulated data.

Required Qualifications

Master’s or PhD in Computer Science, Machine Learning, Applied Mathematics, Physics, Engineering, or a related field.
Hands-on experience with PINNs or scientific machine learning.
Experience with multimodal modeling and/or world model development.
Strong Python skills, with experience in PyTorch or TensorFlow.
Knowledge of neural networks, physical systems, numerical methods, or simulation.

Technical Skills

Python
PyTorch
TensorFlow

Preferred Qualifications

Research or industry experience in automotive, robotics, autonomous systems, or physical AI.
Experience with sensor fusion, differential equations, simulation, or predictive dynamics models.
Relevant research publications or project experience.

Location

Warren, MI (onsite)

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