Machine Learning Engineer

Job Description:

• Build and maintain end-to-end ML pipelines using XGBoost, LightGBM, PyTorch, and TensorFlow.
• Architect scalable training and inference systems for real-time predictions.
• Lead cross-functional ML initiatives and mentor engineering teams.
• Optimize models for demand forecasting, fraud detection, and personalization.
• Apply MLOps best practices and collaborate with DevOps on deployment.
• Process and analyze 10TB+ datasets using distributed computing frameworks.

Requirements:

• 4+ years building production ML systems at scale (100K+ users).
• Expert in XGBoost, LightGBM, and gradient boosting algorithms.
• Strong Python and ML stack experience: PyTorch, TensorFlow, NumPy, Scikit-learn.
• Hands-on experience with agentic AI systems and MCP frameworks.
• Proven track record in ML deployment and MLOps.
• Technical leadership and mentorship experience.

Benefits: