Senior/Lead AI/ML Engineer

About the Position

We are seeking a Senior/Lead AI/ML Engineer to join our team in Europe, Ukraine, focusing on predictive maintenance and asset performance optimization.

Responsibilities

• Design, develop, and deploy machine learning models for predictive maintenance, anomaly detection, and asset health monitoring.
• Build and maintain production-grade ML pipelines for time-series forecasting and sensor/telemetry data processing.
• Collaborate with Data Engineers and Analytics Engineers on data preparation, feature engineering, and model integration.
• Integrate model outputs, risk scores, and predictive insights into operational dashboards and business applications.
• Establish and maintain MLOps processes, including model deployment, monitoring, retraining, and drift detection.
• Research and evaluate new AI/ML approaches, tools, and technologies to improve predictive capabilities and business outcomes.
• Work closely with business and technical stakeholders to translate complex analytical results into actionable recommendations.

Requirements

• 5+ years of experience as a Machine Learning Engineer or Data Scientist.
• Strong Python skills and hands-on experience with Pandas, NumPy, Scikit-Learn, SciPy, and related ML libraries.
• Proven experience with time-series forecasting and predictive modeling techniques (ARIMA, Prophet, XGBoost, LSTM/RNN, etc.).
• Experience working with telemetry, IoT, sensor, or equipment performance data.
• Hands-on experience with Azure Machine Learning, Databricks, MLflow, or similar MLOps platforms.
• Strong SQL skills and experience working with both relational and non-relational databases.
• Experience building and deploying production-ready ML solutions.
• Strong analytical and problem-solving skills with the ability to translate technical insights into business value.

Nice to Have

• Master's or PhD degree in Data Science, Statistics, Engineering, Mathematics, Operations Research, or a related quantitative field.
• Experience in mining, manufacturing, heavy industry, utilities, or other asset-intensive domains.
• Knowledge of Operational Technology (OT) environments and reliability engineering concepts.
• Experience with enterprise asset management systems such as SAP PM or IBM Maximo.
• Familiarity with reliability methodologies such as RCM or FMEA.
• Experience with real-time data processing and anomaly detection on streaming platforms (Kafka, Azure Stream Analytics, etc.).

We Offer

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

not applicable for freelancers