Lead Machine learning Engineer

Role: Lead Machine Learning Engineer

Experience: 5 Years

Location: Chennai

Work Mode: Hybrid

Job Summary:

We are seeking a Machine Learning Engineer to design develop and deploy advanced AI/ML solutions including agentic AI systems and traditional machine learning models for the mortgage servicing and originations domain. This role involves building scalable production-ready ML models on Google Cloud Platform applying classification techniques model optimization and tuning and driving AI-powered automation and decision-making across business processes.

Roles & Responsibilities

• Lead the design development training and deployment of AI/ML models including traditional ML and agentic AI systems.
• Develop classification regression and predictive models using structured and unstructured data.
• Perform model tuning hyperparameter optimization feature engineering and model evaluation to improve accuracy and performance.
• Build and manage scalable data pipelines and ML workflows on Google Cloud Platform.
• Implement monitor and optimize AI/ML models for performance latency scalability and reliability.
• Collaborate with cross-functional teams to integrate AI/ML solutions into business applications.
• Analyze large datasets to derive actionable insights and support data-driven decision-making.
• Develop and maintain automated testing validation and monitoring frameworks for ML models.
• Ensure model reproducibility versioning and lifecycle management in production environments.
• Contribute to MLOps practices including CI/CD pipelines for ML model deployment.
• Document model architectures workflows and ensure adherence to data governance and security standards.
• Stay updated with advancements in machine learning generative AI and LLM technologies applying best practices to enhance solutions.
• Troubleshoot and resolve issues related to model performance deployment and data integration.

Required Skills

• Python for ML model development
• Traditional Machine Learning Concepts (classification regression clustering)
• Model development tuning and optimization
• Generative AI LLMs RAG Prompt Engineering
• MLOps (model deployment monitoring CI/CD)
• Data preprocessing feature engineering and model evaluation

Qualifications & Experience

• 5-8 years of experience in AI/ML model development including traditional ML and advanced AI systems
• Strong hands-on experience in building and deploying ML models in production
• Experience in architecting scalable ML solutions
• Knowledge of advanced MLOps automation and monitoring frameworks
• Understanding of data governance security and compliance
• Ability to mentor junior engineers and provide technical leadership