Lead - AI Engineering (ML, Evaluation & Databricks) (Bengaluru)

Lead - AI Engineering (ML, Evaluation & Databricks) (Bengaluru)

12 Oct
|
IndusInd Bank
|
Bengaluru

12 Oct

IndusInd Bank

Bengaluru

Role Details: Leads the engineering of production-grade AI and ML solutions on Azure Databricks, with accountability for model development, applied statistics, evaluation, lifecycle management and operational quality.

Job Location : Bangalore/Gurugram/Mumbai

OVERALL JOB DESCRIPTION :
AI/ML Solution Engineering
• Lead the end-to-end engineering of AI and machine-learning solutions, from problem formulation and technical design through data preparation, model development, deployment, monitoring and ongoing improvement.
• Design modular and reusable components for feature engineering, training, evaluation, inference, model access, feedback, monitoring and governance rather than building isolated notebook-based solutions.
• Partner with AI Application Engineering teams to integrate predictive models, retrieval components, evaluation services and GenAI capabilities into secure enterprise applications.
• Determine when predictive ML, statistical methods, search, rules, GenAI or a combined engineering approach is most appropriate.

Machine Learning & Applied Statistics




• Engineer production ML solutions across classification, regression, ranking, forecasting, clustering and anomaly detection use cases.
• Apply statistical methods to define targets, sampling strategies, baselines, validation design, metrics, calibration, thresholds and release criteria.
• Identify leakage, bias, class imbalance, confounding, temporal effects and uncertainty and conduct systematic error analysis across relevant business segments.
• Balance model performance with explainability, stability, latency, operational complexity, maintainability and cost.

AI Evaluation Engineering
• Build reusable evaluation frameworks for predictive models, retrieval systems, LLM applications and bounded agentic workflows.
• Create representative labelled and regression datasets covering normal, difficult, edge and adversarial cases and establish measurable production-readiness thresholds.
• Combine deterministic

📌 Lead - AI Engineering (ML, Evaluation & Databricks) (Bengaluru)
🏢 IndusInd Bank
📍 Bengaluru

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