Job Description
Role : Sr AI Engineer
Location : Santa Clara, CA (Onsite)
Position Type : Contract
JOB DESCRIPTION
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.
- Build materials-informatics pipelines combining DFT/MD simulations, high-throughput experiments, and fab/metrology data to learn process–structure–property relationships for materials used in CVD/ALD/etch equipment.
- Develop deep learning models for forecasting thermal, mechanical, chemical, and plasma-compatibility behavior of candidate materials.
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.
Best Regards,
Bismillah Arzoo (AB)