Materials Science Ai Engineer

Location: Santa Clara, CANumber of days onsite - 5 DaysNeed candidates with a PhD (Material Science or Machine learning preferred) Must Have SkillsSkill 1 - Strong proficiency in programming languages like Python and C++.Skill 2 - Experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).Skill 3 - Experience with data cleansing, preprocessing, and feature engineering Good To have SkillsSkill 1 - Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems

Key Responsibilities: Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems. Aggregate, process, transform and quality-control experimental and simulation data for modeling and analysis. Design, develop, and maintain data workflows to support materials informatics initiatives. Optimize data pipelines and model execution on parallel cloud systems (e.g., Azure, GCP, AWS).Collaborate with materials scientists, chemists, and software engineers to integrate analytics and predictive modeling into core R&D workflows. Document code, workflows, and best practices to support reproducible research. Apply AI and data analytics to optimize material synthesis and processing parameters in real-time, minimizing defects, improving consistency.

Technical Skills: Strong proficiency in programming languages like Python and C++.Experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).Knowledge of generative modeling techniques and architectures (e.g., GANs, VAEs, transformers).Knowledge of MLOps, model deployment pipelines, and CI/CD.Experience with data cleansing, preprocessing, and feature engineering