AI & Optimization Engineer

This is a fully remote position, open to applicants in Italy.

📋 Description

• Define and spearhead the AI strategy for MOS & MDK, emphasizing operational efficiency and quantifiable business results.

• Transform operational challenges into data and optimization issues that AI models can address.

• Develop best-practice frameworks for AI systems that are scalable and ready for production.

• Create a standardized data baseline/schema for telemetry and events across all mining sites.

• Ensure that data is structured, normalized, labeled, and accessible for AI/ML applications.

• Collaborate with backend engineers to advance the data pipeline and integration standards.

• Construct and implement ML/AI and optimization models, including performance optimization, anomaly detection, predictive failure and maintenance, energy efficiency insights, and operational automation recommendations.

• Continuously assess and enhance model performance once deployed in production.

• Work in conjunction with MOS & MDK engineering teams to integrate AI models into platform workflows and APIs.

• Foster a culture of data-driven decision-making and efficiency within the Mining Software team.

• Keep abreast of trends in AI, optimization, and industrial analytics.

⛳️ Requirements

• 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 extensive time-series datasets.

• Strong command of Python and contemporary ML frameworks (e.g., PyTorch, TensorFlow, Scikit-Learn).

• Proficient in JavaScript/TypeScript (Node.js ecosystem).

• Familiarity with containerized workloads (Docker).

• Experience in developing and deploying time-series, anomaly detection, classification, and predictive models for mechanical, electromechanical, or hardware-intensive equipment/systems within production environments.

• 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 within production systems, including managing model drift and adapting to evolving operating conditions.

• Excellent English communication skills with the ability to collaborate in distributed teams.

🏝️ Benefits

• Health insurance

• Remote work options