Description

You will design, implement, and maintain production-grade AI solutions, including ML, DL, and LLM models, ensuring scalable and secure integrations.

This role is on-site.

Responsibilities

• Lead the design and implementation of productionized ML, DL, and LLM solutions that meet non-functional business requirements.
• Develop and maintain CI/CD release pipelines to automate build and deployment procedures for data science teams.
• Monitor deployed model performance and provide recommendations to optimize ML/LLM configurations.
• Troubleshoot and diagnose production deployments of AI solutions and manage API endpoints.
• Collaborate with DevOps and Infrastructure teams to ensure smooth deployment and promote MLOps practices.

Required Skills

• 7+ years of professional experience in AI Ops or ML engineering.
• Proficiency in Python, SQL, R, and Scala.
• Hands-on experience with AI/ML models and deploying API endpoints.
• Expertise in ML engineering frameworks such as ML Flow, Airflow, Langchain, Langfuse, or LLM Guard.
• Experience with cloud-based tools including Azure, AWS, Kubernetes, and Docker.
• Strong 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.

Key Skills

Education

Any Graduate