Advanced Analytics Research Scientist - AI for Control

Rockwell Automation is a global technology leader focused on helping the world's manufacturers be more productive, sustainable, and agile. With more than 28,000 employees who make the world better every day, we know we have something special. Behind our customers - amazing companies that help feed the world, provide life-saving medicine on a global scale, and focus on clean water and green mobility -our people are energized problem solvers that take pride in how thework we do changes the world for the better.

We welcome all makers, forward thinkers, and problem solvers who are looking for a place to do their best work. And if that's you we would love to have you join us!

Job Description

Rockwell Automation's AI Center of Excellence in Austin Texas has a position available for data scientist with problem solving, control, and optimization background. You are expected to contribute to the development of AI-driven control and optimization technologies to pave the way for transition from automation to autonomy. Your will create a partnership to test new AI-driven solutions in the real-world is a major requirement for this position. You will be reporting to the Director, Artificial Intelligence Center of Excellence.

Your Responsibilities:

• Participate in the algorithmic development, testing, and POC deployment of AI-driven control and optimization solutions.
• Capture the feedback from POC engagements and incorporate lessons learned back into the AI engine.
• Create required test scenarios/plans to ensure complete testing of AI solution and its components.
• Architect AI solution for integration with real-time control loop in Industrial Automation applications.
• Collaborate with product owners and partners to ensure understanding of AI architecture with priorities.
• Monitor industry trends and identify opportunities to implement new technologies.
• Help create a culture of openness and transparency.
• Build relationships with technical partners across the organization.

The Essentials - You Will Have:

• Bachelor's Degree in Relevant Field

The Preferred - You Might Also Have:

• Bachelor's, Master's, or Ph.D in Computer Science, Engineering, Applied Mathematics, or related fields with a focus on AI and deep learning.
• Typically requires minimum 5 years relevant experience
• Attention to detail, problem- solving skills.
• Familiarity with edge computing for deploying AI models at the edge.
• Familiarity with the AI/ML-driven modeling and first-principles modeling of complex systems is a must
• Familiarity with optimization theory (e.g., LP, NLP, MILP, MINLP)
• Experience with reinforcement learning, Generative AI concepts and techniques.
• Programming skills in Python, and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
• Experience with PLC programming is a plus
• Enthusiasm towards learning new technologies.

What We Offer:

• Health Insurance including Medical, Dental and Vision
• 401k
• Paid Time off
• Parental and Caregiver Leave
• Flexible Work Schedule where you will work with your manager to enjoy a work schedule that can be flexible with your personal life.
• To learn more about our benefits package, please visit at www.raquickfind.com.

At Rockwell Automation we are dedicated to building a diverse, inclusive and authentic workplace, so if you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right person for this or other roles.

This position is part of a job family. Experience will be the determining factor for position level and compensation.

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We are an Equal Opportunity Employer including disability and veterans.

If you are an individual with a disability and you need assistance or a reasonable accommodation during the application process, please contact our services team at +1 (844) 404-7247.

Rockwell Automation's hybrid policy aligns that employees are expected to work at a Rockwell location at least Mondays, Tuesdays, and Thursdays unless they have a business obligation out of the office.