Kafka Real Time Analytics Engineer

Materials Science AI Engineer (PhD Required) Location: Santa Clara, CA Work Mode: 5 Days Onsite Overview We are seeking an Materials Science AI Engineer (PhD Required) to join our team in developing and supporting materials discovery and design initiatives. The ideal candidate will have strong experience building AI-based solutions, including neural network architectures, attention mechanisms, multi-modal learning, data aggregation and structuring, statistical modeling, and cloud-based compute for parallelized, scalable, and automated workflows.

• Strong proficiency in programming languages such as Python and C++
• Experience with machine learning and deep learning frameworks (e.g., PyTorch , TensorFlow )
• Experience with data cleansing, preprocessing, and feature engineering
• Ability to design, develop, and deploy multi-modal AI/ML and hybrid physics-based models to solve cutting-edge materials science and design problems

• Design, develop, and deploy multi-modal AI/ML and hybrid physics-based models to solve groundbreaking problems in materials physics and design
• 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, Google Cloud Platform, 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 to minimize defects and improve consistency

• PhD in Materials Science, Computer Science, Engineering, Applied Mathematics, or a related technical field
• 2 4 years of experience (depending on degree level) in data science, AI, machine learning, or data engineering
• Strong foundation in materials science to define meaningful AI-driven research problems
• Expertise in Python and data science libraries (e.g., pandas, NumPy, scikit-learn, PyTorch, TensorFlow)
• Experience with cloud-based computing environments and tools for parallel or distributed computing
• Strong problem-solving and communication skills

For applications and inquiries, contact: hirings@openkyber.com