Description

You will design and implement productionized AI solutions, including ML, DL, and LLM models, to solve business problems through scalable and secure integration.

Responsibilities

• Lead the design and implementation of scalable, resilient, and secure productionized model solutions.
• Develop and maintain CI/CD release pipelines to automate build and deployment procedures for data science teams.
• Monitor and maintain deployed model performance, providing recommendations for ML/LLM configuration optimization.
• Troubleshoot and diagnose production deployments of AI solutions and manage API endpoints.
• Mentor junior AI Ops developers and promote ML Ops practices across the data science community.

Required Skills

• 5+ years of experience in AI Ops, ML engineering, data science, data engineering, or DevOps.
• Proficiency in Python, SQL, R, and Scala.
• Hands-on experience with AI Ops, ML Ops, and ML Engineering.
• Experience with Kubernetes and Docker.
• Working knowledge of cloud environments including Azure and AWS.
• Experience with APIMs and deploying API endpoints.
• Practical understanding of machine learning techniques, algorithms, and predictive modeling.
• Ability to design scalable Model as a Service solutions.
• Experience with Agile and product-oriented development.

Preferred Skills

• Bachelor’s degree in Statistics, Mathematics, Engineering, Data Science, or Computer Science.
• 7+ years of professional experience in AI Ops, ML engineering, or related fields.

Key Skills

Education

Any Graduate