AI/ML Architect

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