Key Responsibilities

• Design and implement end-to-end machine learning and deep learning solutions
• Build and maintain data pipelines and data engineering workflows
• Deploy, monitor, version, and retrain ML models using MLOps best practices
• Perform exploratory and predictive analytics on large datasets
• Design and execute experiments including A/B testing
• Evaluate and monitor model performance in production
• Conduct feature engineering and data preparation
• Collaborate with cross-functional teams across energy, manufacturing, or enterprise environments

Requirements

• 6+ years of experience in Machine Learning, Deep Learning, and Statistical Analysis
• Proficiency in Python or R
• Strong SQL skills
• Experience with Statistical Analysis and Hypothesis Testing
• Hands-on MLOps experience (Deployment, Monitoring, Versioning, Retraining)
• Knowledge of Data Engineering Concepts and Data Pipelines
• Experience with Model Performance Evaluation and Monitoring
• Experiment Design and A/B Testing expertise
• Feature Engineering and Data Preparation skills
• Passport mandatory
• Good to have: NLP, LLMs, RAG Architectures, Vector Databases, Prompt Engineering
• Good to have: Experience in Energy, Manufacturing, Oil & Gas, or Large Enterprises

Skills Required