About this role
EY seeks an AI and machine learning leader to establish and scale enterprise AI engineering capabilities on SAP BTP and other cloud platforms. The role spans traditional machine learning and emerging generative AI, with a focus on building teams and delivering predictive, analytical, agentic and autonomous AI solutions. The listed location is Noida, with “Anywhere in Country” also shown as an option. Salary is described as competitive.
Responsibilities
- Lead capability development across machine learning, deep learning, MLOps and LLMOps; define technical standards, frameworks and engineering practices.
- Architect and oversee solutions involving predictive analytics, computer vision, NLP, recommendation systems, intelligent automation and generative AI.
- Establish scalable model development, deployment, monitoring and governance processes. Apply MLOps and LLMOps to improve reliability, traceability, observability and operational performance.
- Mentor AI engineers; work with business and technology stakeholders to identify opportunities and turn them into production solutions. Lead technical reviews and architecture discussions, evaluate emerging tools, and contribute to innovation, technical assets and market-facing initiatives.
Required capabilities:
- Strong experience in machine learning, deep learning, statistical modelling and AI solution engineering, with hands-on Python expertise and familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain or LangGraph.
- Understanding of model training, optimisation, evaluation, deployment, monitoring and lifecycle management; experience establishing MLOps, LLMOps, data science engineering and AI platform practices.
- Knowledge of data engineering, feature engineering, model observability and AI governance; practical experience with foundation models, RAG, AI agents and orchestration frameworks. Understanding of cloud AI services and distributed workloads.
- Technical team leadership, coaching, client and stakeholder management, communication and consulting skills, and the ability to balance research-oriented innovation with enterprise delivery.
Preferred qualifications include building AI teams or centres of excellence; work on large-scale, cross-industry AI programmes; experience with model evaluation, AI risk management and Responsible AI; familiarity with knowledge graphs, multi-agent systems or reinforcement learning; relevant SAP BTP, cloud or AI certifications; and contributions to AI communities, publications, open source, patents or thought leadership.