AI/ML Architect

EY; New Delhi; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

EY in Delhi is seeking a senior AI/ML architect to design scalable AI/ML, Generative AI, and MLOps solutions aligned with business objectives. You will lead development, deployment, and lifecycle management of models and AI platforms, while ensuring governance and security.

You will collaborate with data scientists, engineering teams, and business stakeholders to translate use cases into production-ready solutions, and drive adoption of cloud-based AI services and CI/CD for ML.

Qualifications

• Experience designing scalable AI/ML architectures and platforms.
• Proficiency in Generative AI, LLMs, RAG, prompt engineering.
• Strong Python programming and ML framework expertise (TensorFlow, PyTorch).
• Hands-on with cloud AI services (Azure, AWS, Google Vertex AI).
• Experience with MLOps, model monitoring, and CI/CD for ML pipelines.
• Knowledge of data engineering, feature stores, and vector databases.
• Familiarity with containerization (Kubernetes, Docker) and API design.

Responsibilities

• Design and architect scalable AI/ML, Generative AI, and MLOps solutions.
• Lead development, deployment, and lifecycle management of ML models and AI platforms.
• Establish AI governance, model security, and responsible AI practices.
• Collaborate with stakeholders, data scientists, and engineering to translate use cases into production-ready solutions.
• Drive adoption of cloud-based AI services, automation frameworks, and emerging AI tech.
• Provide technical leadership, architecture reviews, and mentorship to AI/ML teams.

Skills

ML & DL

Generative AI

Python

Cloud AI platforms

MLOps

Data Engineering

Kubernetes

Tools

TensorFlow

PyTorch

Scikit-learn

Azure AI

AWS AI/ML

Vertex AI

Job description

Role & responsibilities

• Design and architect scalable AI/ML, Generative AI, and MLOps solutions aligned with business objectives.
• Lead the development, deployment, and lifecycle management of machine learning models and AI platforms.
• Establish AI governance, model security, responsible AI practices, and compliance standards.
• Collaborate with business stakeholders, data scientists, and engineering teams to translate use cases into production-ready solutions.
• Drive adoption of cloud-based AI services, automation frameworks, and emerging AI technologies.
• Provide technical leadership, architecture reviews, and mentorship to AI/ML development teams.

Preferred candidate profile

• Machine Learning, Deep Learning, NLP, Computer Vision, Predictive Analytics
• Generative AI, LLMs, RAG, Prompt Engineering, AI Agents
• Python, TensorFlow, PyTorch, Scikit-learn
• Azure AI, AWS AI/ML Services, Google Vertex AI
• MLOps, Model Monitoring, CI/CD for ML
• Data Engineering, Feature Stores, Vector Databases
• Kubernetes, Docker, API Design & Integration