Industrial AI & Automation Systems Engineer

Fortive

Industrial AI & Automation Systems Engineer at Ralliant Corporation shaping digital manufacturing with AI and automation initiatives across production processes.

Posted 7/6/2026full-timeKezmarok • 🇸🇰 SlovakiaMid-LevelSenior💰 €21,100 - €39,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in identifying and implementing AI-enabled solutions within manufacturing processes, utilizing structured improvement methods such as Lean and FMEA. Proficient in collaborating with cross-functional teams to develop decision-support tools and enhance operational efficiency.

Highest-signal resume keywords

AI-Enabled Solutions DevelopmentLean MethodologyManufacturing Systems KnowledgeCross-Functional CollaborationMachine Vision Technologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LeanFMEARoot Cause AnalysisStatistical Process ControlPythonSQLPower BIIndustrial Communication ProtocolsEmbedded SystemsDigital Application Tools

Soft Skills

Systems-Thinking CapabilityStructured Problem SolvingCollaboration

Tools & Technologies

MESERPSCADAIoTPower PlatformLow-Code/No-Code ToolsModern Analytics Platforms

Industry Keywords

Digital TransformationAutomationManufacturing EngineeringProduction SystemsSmart SensingPredictive MaintenanceRobotics Support

Tech Stack

Tools & technologies

ERPIoTPythonSQL

About the role

Key responsibilities & impact

Identify and support AI, automation, and digitalisation opportunities across manufacturing and support processes
Analyse production systems and workflows to identify inefficiencies, variation, and improvement potential
Develop and help implement AI-enabled solutions using data from manufacturing, quality, and business systems
Contribute to practical physical AI applications such as machine vision, predictive maintenance, robotics support, and smart sensing
Work with cross-functional teams to ensure solutions address operational needs and can be adopted successfully
Support digital transformation projects from idea through pilot, validation, implementation, and sustainment
Create dashboards, workflows, and decision-support tools that improve visibility and problem solving
Apply structured improvement methods such as Lean, root cause analysis, FMEA, and statistical thinking
Help ensure that solutions are secure, maintainable, and aligned with technical, safety, and organisational standards
Keep up to date with relevant developments in AI, automation, and digital manufacturing, and assess their practical value for the site

Requirements

What you’ll need

Degree in Industrial Engineering, Chemical Engineering, Manufacturing Engineering, or a related engineering discipline
Experience in a manufacturing, production, process, or industrial environment
Strong systems-thinking capability and a structured approach to problem solving
Interest in applying AI, automation, and digital tools to practical manufacturing challenges
Knowledge of continuous improvement methods such as Lean, Six Sigma, root cause analysis, SPC, or FMEA
Familiarity with manufacturing systems and data environments such as MES, ERP, SCADA, IoT, SQL, or Power BI
Ability to work collaboratively across functions and translate operational needs into scalable solutions
Good command of English, both written and spoken.
Exposure to physical AI technologies such as machine vision, robotics, smart sensors, edge AI, or connected equipment (preferred qualification)
Working knowledge of digital application tools such as Power Platform, Python, low-code/no-code tools, or modern analytics platforms (preferred qualification)
Experience with programming, industrial communication protocols, or embedded systems would be an advantage depending on application needs (preferred qualification)

Benefits

Comp & perks

Health insurance (not explicitly mentioned but commonly offered)
Retirement plans (not explicitly mentioned but commonly offered)
Paid time off (not explicitly mentioned but commonly offered)
Flexible work arrangements (not explicitly mentioned but commonly offered)
Professional development (not explicitly mentioned but commonly offered)
Bonuses (not explicitly mentioned but commonly offered)
Stock options (not explicitly mentioned but commonly offered)
Equipment allowances (not explicitly mentioned but commonly offered)
Wellness programs (not explicitly mentioned but commonly offered)