Advanced Analytics Research Scientist – Industrial Edge Intelligence

Rockwell Automation

. Develop AI-native industrial systems capable of real-time reasoning and decision making, adaptive process optimization, autonomous operational behaviors, continuous learning from operational data, and intelligent coordination across distributed industrial assets .

Posted 10/14/2026full-timeAustin • Texas • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing AI-native industrial systems with a focus on real-time decision making, adaptive process optimization, and integration with automation systems. Proficient in deploying AI solutions on edge compute platforms, utilizing machine learning, reinforcement learning, and advanced analytics.

Highest-signal resume keywords

Edge AI SystemsMachine Learning Systems EngineeringAutonomous SystemsPython ProgrammingIndustrial Automation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Application DevelopmentReinforcement LearningControl SystemsTime-Series AnalyticsAnomaly DetectionDigital TwinsSimulation EnvironmentsEmbedded SystemsGPU-Accelerated ComputingStreaming Analytics

Tools & Technologies

AI/ML FrameworksEdge Inference OptimizationResource-Constrained EnvironmentsOperational Technology (OT)Robotics Platforms

Certifications & Qualifications

Bachelor's Degree in Relevant Field

Industry Keywords

Industrial AICyber-Physical SystemsDistributed AI ArchitecturesOperational InfrastructureEvent-Driven Intelligence

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Develop AI-native industrial systems capable of real-time reasoning and decision making, adaptive process optimization, autonomous operational behaviors, continuous learning from operational data, and intelligent coordination across distributed industrial assets
Design and deploy AI solutions on edge compute platforms with advanced CPU/GPU acceleration capabilities
Build architectures combining generative AI and small language models, machine learning and reinforcement learning, optimization and control systems, streaming analytics and event-driven intelligence, and distributed and edge-native AI inference
Ensure low-latency AI execution 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 AI research, controls engineering, embedded systems, and industrial operations teams
Report to the Director AI

Requirements

What you’ll need

Bachelor's Degree in Relevant Field
Typically requires 5+ years relevant experience
Background in Edge AI systems
Background in machine learning systems engineering
Background in autonomous systems
Background in industrial AI
Background in 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
Familiarity with GPU-accelerated computing
Familiarity with streaming and real-time systems
Familiarity with distributed AI architectures
Familiarity with control and optimization systems
Industrial automation or control systems experience
Robotics and autonomous platforms experience
Reinforcement learning or adaptive control experience
Time-series analytics and anomaly detection experience
Embedded systems and edge deployment toolchains experience
Digital twins and simulation environments experience
Vision-language or multimodal AI systems experience
Cyber-physical systems and operational technology (OT) experience

Benefits

Comp & perks

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