Machine Learning Engineer

Qualifications

• Have Master’s degree in the field of AI / ML and data science with proven ability to design and develop models
• 6+ years of experience in data science and machine learning, with at least 3+ years in ML engineering roles.
  
  
• Proven experience in end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.
  
  
• Strong programming skills in Python (pandas, scikit-learn, TensorFlow/PyTorch, etc.).
  
  
• Strong knowledge in NoSQL databases (any experience in Graph database is desirable)
• Experience with MLOps tools: MLflow, TFX, Airflow, Kubeflow, or similar.
  
  
• Familiarity with cloud platforms (GCP, AWS, or Azure) for ML deployment.
  
  
• Knowledge of data science techniques including supervised/unsupervised learning, NLP, time series, etc.
  
  
• Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
  
  
• Strong understanding of AI governance, model risk management, and regulatory requirements in AI.
  
  
• Ability to communicate technical concepts to non-technical stakeholders.