AI Scientist/Engineer

Mandatory Areas

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.