Machine Learning Engineer
Core
Design, develop, deploy, and continuously improve machine learning solutions for advanced materials and steel applications, focusing on production-ready models and product integration.
Role type
Machine Learning Engineer
Builds
Production-ready ML models, data workflows, cloud services, and user-facing product features for the steel industry.
Domain
Industrial materials science, metallurgy, and steel manufacturing.
Deliverable
production ML models | product features
Required skills
Python, pandas, scikit-learn, statistical modeling, machine learning methods, validation strategies, performance metrics, backend/frontend integration basics
Preferred skills
Google Cloud Platform, containerized services, MLOps workflows, Git-based version control, automated testing, continuous integration, physics-informed machine learning, scientific computing
Technologies
Python, pandas, scikit-learn, Google Cloud Platform, Git
Responsibilities
Aggregate, clean, and prepare materials and process data; design and develop ML models; define model assumptions and evaluation metrics; validate and benchmark existing models; develop and maintain cloud-based ML services; monitor production models and troubleshoot issues; integrate ML modules into web applications; support customers with simulations and model outputs.
Seniority
Mid-to-Senior, hands-on IC
