Walk-in || Artificial Intelligence Engineer

Role & responsibilities

• Python

• SQL

• Machine Learning (ML)

• Docker / Kubernetes

• AWS or GCP

Preferred candidate profile

Key Responsibilities:

Key Responsibilities:

• Production Pipelines:

  Build, operationalize, and maintain automated ML/AI pipelines to deliver real-time and batch model inferences at scale.

• Code & Architecture Reviews:

  Participate in design reviews, system code reviews, and structured deployment patterns for critical AI applications.

• Cloud Infrastructure Optimization:

  Manage cloud resources and leverage platforms like Google Cloud Platform (GCP) or AWS to manage model artifacts and data layers efficiently.

• Cross-Domain Integration:

  Work across multiple AI paradigms, including Generative AI, Supervised Learning, Unsupervised Learning, and Reinforcement Learning based on business needs.

• MLOps & Automation:

  Integrate CI/CD concepts specifically tuned for AI applications (AIOps/MLOps) to track versioning, prevent model drift, and automate monitoring.