Staff Data Scientist

Job Overview:

We are seeking a highly skilled and innovative Staff Data Scientist with a background in physics or a related field. This individual will focus on developing machine learning (ML) models to assist in the design of physical systems and evaluate mathematical constructs. You will leverage Informed Neural Networks (INNs), simulations, numerical optimization, and ML Ops practices to integrate ML models into design pipelines and inform upstream and downstream processes. Additionally, you will drive research and execution of new ideas at the intersection of machine learning, computational physics, and mathematics.

Key Responsibilities:

• Develop ML Models: Build ML models to assist in the design of physical systems and evaluation of mathematical constructs.
• Support Design Pipelines: Inform the generation of data and designs in the upstream pipeline and assist the transition of ML models from development to deployment in the downstream pipeline.
• Innovate in ML-Assisted Physics: Research, recommend, and execute new ideas in ML-assisted computational physics and mathematical design.
• Simulations and Optimization: Implement simulations and numerical optimization techniques to drive performance and scalability.
• Collaborate Across Teams: Work with cross-functional teams to develop software solutions using standard practices (e.g., GitHub) and support the integration of models into engineering workflows.

Qualifications:

• Education: PhD or Master’s degree in Physics, Applied Mathematics, Engineering, or a related field.
• Experience with Informed Neural Networks (INNs): Expertise in the development and deployment of INNs and physics-informed ML models.
• ML Ops Proficiency: Experience with ML Ops practices, ensuring smooth transitions from model development to deployment.
• Simulations and Numerical Optimization: Strong experience in simulations and numerical optimization techniques.
• Physics and Machine Learning Expertise: Either deep experience building physics-informed ML models or a strong physics background with robust machine learning expertise.
• Technical Proficiency: Expertise in general-purpose machine learning platforms such as TensorFlow or PyTorch, and domain-specific tools such as NVIDIA Modulus.
• Software Development Skills: Proficiency in Python, NumPy, SymPy, and version control systems like GitHub.