C
Materials Science Ai Engineer
Cardinal Integrated
3 hours ago
Full-time
On-site
Materials Science AI Engineer
Location: Santa Clara, CA - 5D Onsite Duration: 6-12+ Months Contract 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 engineering Good 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 problems We are seeking an AI Scientist/Engineer to join our team in developing and supporting materials discovery and design. The ideal candidate will have strong experience building AI-based solutions for building neural network architecture, attention mechanisms, multi-modal learning, aggregating and structuring training data, statistical theory, and cloud-based compute for parallelized, scalable, and automated workflows. 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 Qualifications
• Graduate or undergraduate degree in Computer Science, Engineering, Applied Mathematics, or a related technical field. • 2-4 years of work experience (depending on educational degree) in data science, AI, machine learning, or data engineering roles. • A strong foundation in the principles of materials science is essential to understand the underlying science and set up meaningful problems for AI. • Expert in Python and data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow or PyTorch). • Expertise in use of cloud-based compute environments and tools for parallel or distributed computing. • Strong problem-solving and communication skills.
Location: Santa Clara, CA - 5D Onsite Duration: 6-12+ Months Contract 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 engineering Good 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 problems We are seeking an AI Scientist/Engineer to join our team in developing and supporting materials discovery and design. The ideal candidate will have strong experience building AI-based solutions for building neural network architecture, attention mechanisms, multi-modal learning, aggregating and structuring training data, statistical theory, and cloud-based compute for parallelized, scalable, and automated workflows. 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 Qualifications
• Graduate or undergraduate degree in Computer Science, Engineering, Applied Mathematics, or a related technical field. • 2-4 years of work experience (depending on educational degree) in data science, AI, machine learning, or data engineering roles. • A strong foundation in the principles of materials science is essential to understand the underlying science and set up meaningful problems for AI. • Expert in Python and data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow or PyTorch). • Expertise in use of cloud-based compute environments and tools for parallel or distributed computing. • Strong problem-solving and communication skills.