Experience Required:
8-10 years in IT, with a minimum of 8 years focused on AI/ML solutions architecture, development, and deployment.

Key Responsibilities:

• Architect and design robust, large-scale AI/ML solutions across multiple domains, including Generative AI.

• Lead and oversee the complete machine learning lifecycle, encompassing data ingestion, feature engineering, model development, deployment, and continuous monitoring.

• Partner with business and technical stakeholders to translate requirements into scalable and efficient ML systems.

• Establish and enforce best practices, standards, and governance frameworks for ML pipelines, MLOps, and data platform management.

• Provide mentorship and technical guidance to data scientists, ML engineers, and solution architects.

• Assess emerging AI/ML technologies and drive their adoption within enterprise environments.

• Ensure AI/ML solutions meet security, compliance, and performance benchmarks.

Required Skills & Qualifications:

• Deep expertise in Generative AI, Agentic AI, machine learning, deep learning, NLP, and big data ecosystems.

• Proficiency with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn; cloud AI platforms including AWS, Azure, and GCP; and MLOps tools like Kubeflow, MLflow, Airflow, Docker, and Kubernetes.

• Strong understanding of data architecture, API design, and scalable microservices.

• Hands-on programming experience in Python or equivalent languages.

• Proven experience delivering enterprise-scale AI/ML solutions.

• Excellent leadership abilities, with strong stakeholder management and communication skills.