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

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

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

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