Senior Machine Learning Engineer

Tasks

• Apply MLOps best practices
• Architect scalable training and inference systems
• Build end-to-end machine learning pipelines
• Deploy machine learning models with DevOps
• Lead machine learning initiatives
• Mentor engineering teams
• Optimize models for demand forecasting and fraud detection
• Optimize models for personalization
• Process and analyze large-scale datasets

Perks/Benefits

• Career growth opportunities
• Hybrid work
• Mentorship
• Remote options

Skills/Tech-stack

Demand forecasting | Distributed Computing | Fraud Detection | Gradient boosting | LightGBM | MLOps | Machine Learning | NumPy | Personalization | PyTorch | Python | Real Time | Real-time Inference | Scikit-learn | TensorFlow | XGBoost