Description

You will lead the design and implementation of AI and ML architectures for large-scale enterprise applications.

You will own the end-to-end AI architecture, selecting technologies from open-source and commercial offerings. You will lead and mentor a team of data scientists, driving collaboration and continuous learning. You will align technical implementations with stakeholder requirements and future business needs. You will develop best practices for the ML lifecycle, including feature engineering, model management, MLOps, and monitoring. You will manage ML and deep learning workflows across data management, governance, and production deployment.

Responsibilities

• Design AI architecture and select technologies from open-source and commercial offerings.
• Lead and mentor a team of data scientists to drive collaboration and continuous learning.
• Align technical implementations with stakeholder requirements and future business needs.
• Develop best practices for the ML lifecycle, including feature engineering, model management, MLOps, and monitoring.
• Manage ML and deep learning workflows across data management, governance, and production deployment.

Required Skills

• 15+ years of experience in solutions architecture or equivalent technical roles.
• Expertise in AI/ML domains, including multimodal ML, model evaluation, and fine-tuning.
• Deep understanding of MLOps and MLSecOps.
• Proficiency in Python and R for advanced analytics.
• Hands-on experience with Deep Learning frameworks like TensorFlow.
• Strong knowledge of ML techniques including neural networks, random forest, and support vector machines.
• Experience with ML training, inference, and data engineering.
• Practical knowledge of Data Warehouse, Data Lake, and Reporting systems.
• Proven ability in estimation and proposal creation.

Preferred Skills

• Experience in Life Science, Manufacturing, BFSI, or Energy and Utilities verticals.

Key Skills

Education

Any Gradute