Industrial AI Expert
At a Glance
- Category
- 💻 Technology
- Level
- Mid-Level
- Type
- Full-time
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Overview:
The Industrial AI Expert is responsible for designing, developing, deploying, and managing advanced
Industrial AI solutions across multiple industrial domains and use cases. The role serves as a subject
matter expert in Industrial AI, applying deep technical expertise to build scalable, production-ready AI
applications that improve operational performance, reliability, safety, and efficiency. The position
focuses on the end-to-end engineering lifecycle of Industrial AI products, including solution
architecture, model development, deployment, integration, monitoring, and continuous optimization.
The role collaborates closely with cross-functional teams and provides technical guidance and
knowledge sharing while remaining an individual contributor without direct people management
responsibilities.
Key Responsibilities:
- Design, develop, deploy, and maintain Industrial AI applications and products across diverse
industrial use cases and operational environments.
- Engineer and implement AI and machine learning solutions for predictive maintenance,
anomaly detection, frontline diagnostics, corrosion prediction, production optimization, and
energy optimization.
- Develop intelligent digital assistants and autonomous operational workflows that enhance
industrial decision-making and operational efficiency.
- Translate business requirements and operational challenges into scalable, production-grade
AI solutions and technical architectures.
- Design and implement data pipelines, feature engineering processes, and model deployment
frameworks that support reliable AI operations.
- Integrate AI solutions with industrial systems, operational technologies, and enterprise
platforms while ensuring interoperability and scalability.
- Monitor model performance, manage model lifecycle activities, and continuously optimize
solutions to maintain accuracy and business value.
- Apply MLOps and AI engineering best practices to improve solution reliability, maintainability,
and deployment efficiency.
- Conduct technical assessments, proof-of-concepts, and feasibility studies for emerging
Industrial AI technologies and use cases.
- Troubleshoot complex technical issues and provide expert guidance on AI solution design,
implementation, and optimization.
- Contribute to engineering standards, reusable frameworks, and best practices to promote
technical excellence and knowledge sharing across teams.
- Collaborate with domain experts, data engineers, product teams, and business stakeholders
to ensure successful solution delivery and adoption.
Qualifications:
Education:
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Computer
Engineering, Electrical Engineering, Industrial Engineering, or related discipline (Master is
preferred)
- Professional certifications in Artificial Intelligence, Machine Learning, Cloud Platforms, Data
Engineering, or MLOps are advantageous
Experience:
- 8–12 years of experience software engineering, data science, artificial intelligence, or machine
learning engineering.
- Demonstrated experience in developing and deploying Industrial AI solutions in industrial,
manufacturing, energy, utilities, or asset-intensive environments.
- Hands-on experience across the full AI solution lifecycle, from data acquisition and model
development to deployment and operational monitoring.
- Experience delivering production-grade AI applications involving industrial analytics and
operational optimization use cases.
Skills & Competencies:
- Artificial Intelligence and Machine Learning Engineering
- Industrial Analytics and Predictive Modeling
- MLOps and AI Lifecycle Management
- Cloud-Based AI Platforms and Distributed Computing
- AI Solution Architecture and Systems Integration
- Industrial Data Platforms and Operational Technologies
Requirements
- •Bachelor’s degree in Computer Science, AI, Data Science, Computer Engineering, Electrical Engineering, Industrial Engineering, or related discipline
- •Master's degree preferred
- •8–12 years of experience in software engineering or data science
- •Expertise in designing, developing, and deploying Industrial AI applications
- •Experience with predictive maintenance, anomaly detection, and production optimization
- •Ability to translate business requirements into technical architectures
- •Proficiency in data pipelines, feature engineering, and model deployment frameworks
- •Knowledge of MLOps and AI engineering best practices
Nice to Have
- •Professional certifications in AI, Machine Learning, Cloud Platforms, Data Engineering, or MLOps
Responsibilities
- •Design, develop, deploy, and maintain Industrial AI applications across diverse use cases
- •Engineer ML solutions for predictive maintenance, anomaly detection, and energy optimization
- •Develop intelligent digital assistants and autonomous operational workflows
- •Design and implement data pipelines and model deployment frameworks
- •Integrate AI solutions with industrial systems and enterprise platforms
- •Monitor model performance and manage the full model lifecycle
- •Conduct technical assessments, proof-of-concepts, and feasibility studies
- •Collaborate with domain experts and stakeholders to ensure solution delivery
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