Operating Engineer

KRDL USA INC•Lincolnshire, IL

10d•Hybrid

About The Position

We are seeking an Operating Engineer to join our team! As an Operating Engineer, you will be maintaining and repairing equipment both on- and off-site as needed, keeping repair logs, and tracking all equipment changes and needs. You will also log any equipment needs or replacements, make minor building or structural repairs, and closely follow all safety recommendations and regulations. The ideal candidate has previous experience in a similar role, the ability to work quickly but safely, and can maintain strong records of maintenance.

Requirements

Previous experience in a similar position is desired
Working knowledge of maintenance, and the ability to learn new equipment and tools
Strong communication and interpersonal skills
Bachelor's Degree or Master's Degree

Responsibilities

AI Strategy & Solution Design
Design, develop, and implement AI/ML solutions aligned with business objectives and enterprise strategy.
Translate business problems into AI-driven use cases and technical architectures.
Collaborate with business leaders, product owners, and domain experts to identify high-value AI opportunities.
Define AI roadmaps, feasibility assessments, and proof-of-concept (PoC) initiatives.
Model Development & Engineering
Build, train, evaluate, and deploy machine learning, deep learning, and generative AI models.
Select appropriate algorithms, frameworks, and tools (e.g., TensorFlow, PyTorch, scikit-learn, LLMs).
Perform feature engineering, data preprocessing, and model optimization.
Ensure models are scalable, efficient, and production-ready.
Data Analysis & Management
Work closely with data engineers to source, clean, and manage structured and unstructured data.
Analyze large datasets to uncover patterns, trends, and actionable insights.
Ensure data quality, governance, privacy, and compliance standards are met.
Leverage cloud and big-data platforms for AI workloads.
Deployment & MLOps
Implement CI/CD pipelines for model training, testing, and deployment.
Monitor model performance, drift, bias, and accuracy in production environments.
Automate retraining, versioning, and lifecycle management of AI models.
Integrate AI solutions into existing enterprise systems and workflows.
Responsible & Ethical AI
Ensure AI solutions adhere to ethical AI principles, fairness, transparency, and explainability.
Identify and mitigate bias, risk, and unintended consequences in AI systems.
Support governance, auditability, and regulatory compliance (e.g., data protection, AI regulations).
Collaboration & Stakeholder Engagement
Partner with cross-functional teams including IT, Security, Legal, Compliance, and Business Units.
Communicate AI concepts, results, and recommendations to non-technical stakeholders.
Provide technical guidance and mentorship to junior team members.
Support change management and AI adoption across the organization.
Research, Innovation & Continuous Improvement
Stay current with emerging AI technologies, tools, and industry trends.
Evaluate new AI platforms, frameworks, and methodologies.
Drive innovation through experimentation, research, and continuous learning.
Contribute to AI standards, best practices, and reusable frameworks.
Documentation & Knowledge Sharing
Maintain clear documentation for models, pipelines, and AI solutions.
Create technical and executive-level reports and presentations.
Share knowledge through training sessions, demos, and internal communities of practice.