Description

Lead architectural decisions for cloud, data, and infrastructure portfolios while implementing large-scale AI/ML solutions.

Responsibilities

• Lead architectural decisions for cloud, data, and infrastructure portfolios.
• Design and deploy large-scale machine learning systems in production environments.
• Implement AI/ML solutions within cloud environments using industry best practices for security and patterns.
• Drive MLOps and DataOps lifecycle engineering to ensure robust enterprise adoption.

Required Skills

• 8+ years of hands-on experience in AI/ML application development.
• 5-6 years of experience in AI/ML solution architecture and systems engineering.
• 5+ years of experience working with AWS or Azure.
• Deep understanding of GenAI models including GPT and Llama 3+.
• Expertise in MLOps and DataOps lifecycle engineering.
• Proficiency in Python and AI/ML specific libraries.
• Strong background in machine learning algorithms.
• Experience with AI services for speech, vision, and text.
• Bachelor’s degree in Computer Science or a related field.

Preferred Skills

• Master’s degree in a related field.
• AWS Professional Certification.
• Experience with Data Architecture principles like data mesh, knowledge graphs, or data ontology.

Key Skills

Education

Bachelor's Degree