Rockwell Automation

Advanced Analytics Research Scientist - Industrial Edge Intelligence

United States · Hybrid · Full time

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About the role

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  • EmployerRockwell Automation
  • LocationUnited States
  • Work styleHybrid
  • Employment typeFull time
  • Employer posted

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 the work 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


Job Description

We are looking for a inventive AI engineer/scientist to help build the next generation of AI-native industrial automation systems powered by latest edge compute platforms.

Show full description

You will focus on developing intelligent systems capable of real-time learning, reasoning, optimization, and autonomous operation. These systems operate directly within industrial environments, bringing advanced AI capabilities closer to machines, processes, and operational decision making. You will work at the convergence of edge AI, industrial automation, autonomous systems, embedded intelligence, and real-time operational analytics to help define how you design and operate future industrial systems.

This role focuses on redefining industrial automation through AI-native system design. The company embeds intelligence directly at the edge, making it capable of learning, adapting, and operating autonomously in real-world environments. You will work on frontier challenges involving real-time AI, autonomous operation, optimization, and industrial-scale deployment while helping shape the future of intelligent industrial infrastructure.

You will report to the Director AI and have a hybrid work schedule, working from Austin, TX

Responsibilities

  • Develop AI-native industrial systems capable of:
  • Real-time reasoning and decision making
  • Adaptive process optimization
  • Autonomous operational behaviors
  • Continuous learning from operational data
  • Intelligent coordination across distributed industrial assets
  • Design and deploy AI solutions on latest edge compute platforms with advanced CPU/GPU acceleration capabilities
  • Build architectures that combine:
  • Generative AI and small language models
  • Machine learning and reinforcement learning
  • Optimization and control systems
  • Streaming analytics and event-driven intelligence
  • Distributed and edge-native AI inference
  • Ensure low-latency AI execution directly within industrial environments while balancing performance, reliability, and operational constraints
  • Integrate AI capabilities with industrial automation systems, robotics platforms, sensors, controllers, and operational infrastructure
  • Collaborate with diverse teams spanning AI research, controls engineering, embedded systems, and industrial operations

The Essentials - You Will Have:

  • Bachelor's Degree in Relevant Field

The Preferred - You Might Also Have:

  • Typically requires 5+ years relevant experience
  • Background in the following:
  • Edge AI systems
  • Machine learning systems engineering
  • Autonomous systems
  • Industrial AI
  • Embedded or distributed AI architectures
  • Experience developing and deploying AI applications in resource-constrained or real-time environments
  • Software engineering skills in Python and modern AI/ML frameworks
  • Familiarity with:
  • Edge inference optimization
  • GPU-accelerated computing
  • Streaming and real-time systems
  • Distributed AI architectures
  • Control and optimization systems
  • Bridge advanced AI concepts with practical deployment in operational environments
  • Curiosity, creativity, and a passion for building intelligent systems that interact directly with the physical world

Bonus Experience

  • Industrial automation or control systems
  • Robotics and autonomous platforms
  • Reinforcement learning or adaptive control
  • Time-series analytics and anomaly detection
  • Embedded systems and edge deployment toolchains
  • Digital twins and simulation environments
  • Vision-language or multimodal AI systems
  • Cyber-physical systems and operational technology (OT)

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.

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

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.

#LI-PD1

#LI-hybrid

#lifeatROK

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.

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  • USD a year, after annualising126,000–423,000 (39 listings, 14 employers)

At a glance

  • Work styleHybrid
  • Employment typeFull time
  • Employer posted
  • Added to ROLIVA
  • Last checked

Skills in this posting

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Python Machine learning

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