AI/ML Engineer

OverviewWe are seeking an AI / Machine Learning Engineer to design, build, deploy, and govern scalable ML and AI solutions across the enterprise. This role combines hands‑on model development with strong ownership of AI governance, risk management, and responsible AI practices to ensure models are explainable, secure, compliant, and production‑ready.Key ResponsibilitiesDesign, develop, train, and deploy machine learning and AI models for structured and unstructured data use casesBuild end‑to‑end ML pipelines including data ingestion, feature engineering, training, evaluation, deployment, and monitoringImplement MLOps practices for versioning, CI/CD, model lifecycle management, and automated retrainingCollaborate with data engineers, product managers, and business stakeholders to translate requirements into AI solutionsMonitor model performance, drift, bias, and data quality in production environmentsOptimize model accuracy, scalability, latency, and cost efficiencyDevelop reusable ML components, libraries, and frameworks to accelerate deliveryAI Governance & Risk ResponsibilitiesEmbed AI governance controls across the model lifecycle (design, development, testing, deployment, decommissioning)Ensure models meet enterprise standards for explainability, transparency, fairness, and auditabilityImplement model documentation, lineage, and traceability (data sources, features, assumptions, limitations)Perform model validation activities including bias testing, robustness testing, and performance benchmarkingSupport regulatory, compliance, and legal requirements (e.g., model risk management, data privacy, internal audits)Partner with security teams to ensure secure model development and protection of sensitive dataContribute to responsible AI policies, standards, and best practices across the organization