Description

You will design, build, and deploy machine learning and deep learning models in production, managing the underlying infrastructure for scalability and performance.

This role is on-site.

Responsibilities

• Design and implement ML/DL models optimized for performance and scalability.
• Preprocess and analyze large-scale structured and unstructured datasets.
• Build scalable infrastructure for training, deploying, and monitoring ML and LLM models.
• Manage Azure Kubernetes Service (AKS) clusters and containerized workloads.
• Integrate models into production systems via APIs, monitor performance, and trigger retraining.

Required Skills

• 5+ years of experience in machine learning or AI engineering.
• Proficiency in Python.
• Hands-on experience with Azure Machine Learning and Azure OpenAI.
• Experience managing Azure Kubernetes Service (AKS) and Docker.
• Strong understanding of Kubernetes and CI/CD pipelines.
• Knowledge of Azure DevOps for model governance and versioning.
• Experience with LLM fine-tuning, prompt engineering, and model deployment.
• Ability to document model architecture and performance metrics.

Preferred Skills

• Familiarity with MLflow, Terraform, and Prometheus/Grafana.

Key Skills

Education

Any Graduate