AI Scientist – Interpretability and Safety in Industrial Foundation Models
| Company | Rockwell Automation |
|---|---|
| Location | Austin, TX, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Expert or higher |
Requirements
- Bachelor’s Degree in Relevant Field.
Responsibilities
- Design and develop deep learning and generative AI models for various industrial use cases, including predictive maintenance, quality control, supply chain optimization, and robotics automation.
- Collaborate with cross-functional teams to understand operational challenges and build AI-driven solutions that can be deployed in industrial settings.
- Address complex challenges in manufacturing and industrial processes using ML/AI as a technology enabler.
- Integrate AI models into the existing automation workflows for smarter decision-making on the factory floor.
- Develop testing and validation strategies to ensure the reliability, accuracy, and safety of Generative AI models in production.
- Conduct proof-of-concept studies and pilot projects to assess the viability of innovative AI approaches for real-world industrial problems.
- Stay up to date with the latest advancements in AI, machine learning, and deep learning, and evaluate their potential applications in industrial environments.
Preferred Qualifications
- Bachelor’s, Master’s, or Ph.D in Computer Science, Engineering, Applied Mathematics, or related fields with a strong focus on AI and deep learning.
- Typically requires minimum 8 years relevant experience.
- Strong programming skills, particularly in Python, and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
- Experience with reinforcement learning, Generative AI concepts and techniques.
- Ability to work collaboratively in a fast-paced team environment.
- Attention to detail, problem-solving skills.
- Familiarity with edge computing for deploying AI models at the edge.