
AI & Optimization Engineer
Posted May 23

Posted May 23
This is a fully remote position, open to applicants in Poland.
• Define and spearhead the AI strategy for MOS & MDK, emphasizing operational efficiency and tangible business results.
• Transform operational challenges into data-centric and optimization tasks that AI models can effectively address.
• Develop best-practice frameworks to ensure scalable, production-ready AI systems.
• Create a standardized data baseline/schema for all mining-site telemetry and event data.
• Guarantee that data is structured, 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 environment.
• Partner with MOS & MDK engineering teams to integrate AI models into platform workflows and APIs.
• Ensure that models are efficient, reliable, interpretable, and maintainable.
• Work alongside site-operations teams to validate outcomes and collect feedback.
• Align with leadership on the AI roadmap, priorities, impact measurement, and KPIs.
• Clearly document systems, architecture, and modeling assumptions.
• Foster a data-driven, efficiency-oriented culture within the Mining Software team.
• Keep abreast of trends in AI, optimization, and industrial analytics.
• 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 positions.
• Demonstrated experience in designing data models/schemas/baselines for large-scale, time-series-dominant datasets.
• High proficiency in Python and contemporary ML frameworks (e.g., PyTorch, TensorFlow, Scikit-Learn).
• Strong skills 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 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 adapting to evolving operational conditions.
• Excellent English communication skills and the ability to collaborate effectively within distributed teams.
• Health insurance
• Flexible working arrangements
EverAI
10x.Team
EverAI
Invisible Technologies
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