Materials Science Ai Engineer
Tranzeal Inc.Santa Clara, CA
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Overview
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Job Description
Job Title:Materials Science Ai EngineerLocation: Santa Clara, CANumber of days onsite – 5 DaysNeed candidates with a PhD (Material Science or Machine learning preferred) Must Have Skills Skill 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 engineeringGood To have Skills Skill 1 – Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problemsKey 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
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This job at Tranzeal Inc. is located in Santa Clara, CA, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
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