
AI & Optimization Engineer
Posted May 21

Posted May 21
This is a fully remote position, open to applicants in Ireland.
• Define and spearhead the AI strategy for MOS & MDK, concentrating on operational efficiency and quantifiable business results.
• Convert operational challenges into data and optimization issues that AI models are capable of addressing.
• Develop best-practice frameworks for scalable, production-ready AI systems.
• Create a standardized data baseline/schema for all mining-site telemetry and events.
• Ensure data is organized, normalized, labeled, and accessible for AI/ML applications.
• Collaborate with backend engineers to enhance the data pipeline and integration standards.
• Construct and implement ML/AI and optimization models such as performance optimization, anomaly detection, predictive maintenance, energy-efficiency insights, and operational automation recommendations.
• Continuously assess and enhance model performance in a production setting.
• Partner with MOS & MDK engineering teams to integrate AI models into platform workflows and APIs.
• Work alongside site-operations teams to validate outcomes and collect feedback.
• Coordinate with leadership on the AI roadmap, priorities, impact tracking, and KPIs.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, Engineering, Statistics, or a related field.
• Over 3 years of experience in AI/ML, data science, or applied optimization roles.
• Demonstrated experience in designing data models/schemas/baselines for large-scale, time-series-heavy datasets.
• Strong expertise in Python and contemporary ML frameworks (e.g., PyTorch, TensorFlow, Scikit-Learn).
• Proficient in JavaScript/TypeScript (Node.js ecosystem).
• Familiar with containerized workloads (Docker).
• Background in developing and deploying time-series, anomaly detection, classification, and predictive models for mechanical, electromechanical, or hardware-intensive equipment/systems in production settings.
• Solid understanding of signal processing and feature extraction for sensor data (e.g., electrical, thermal, vibration, or telemetry signals).
• Strong grasp of optimization techniques (linear/non-linear programming, simulation, decision systems, etc.).
• Experience in deploying, monitoring, and maintaining AI models in production systems, including managing model drift and evolving operating conditions.
• Excellent English communication skills with the ability to collaborate effectively in distributed teams.
• Competitive salary
• Remote work options
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