Advanced Analytics Research Scientist - Industrial Edge Intelligence

Rockwell Automation•Austin, TX

6d•Hybrid

About The Position

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.

Requirements

Bachelor's Degree in Relevant Field

Nice To Haves

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)

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