Consultant Software Engineer - AI Platform

Role Overview

As an AI Ops Expert, you will have full ownership for deliverables with greater defined quality standards, adhering to defined timelines and budgets.

Responsibilities

• Design, implement, and manage AIops solutions to automate and optimize AI/ML workflows.
• Collaborate with data scientists, engineers, and other stakeholders to ensure seamless integration of AI/ML models into production.
• Monitor and maintain the health and performance of AI/ML systems.
• Develop and maintain CI/CD pipelines for AI/ML models.
• Implement best practices for model versioning, testing, and deployment.
• Troubleshoot and resolve issues related to AI/ML infrastructure and workflows.
• Stay up-to-date with the latest AIops, MLOps, and Kubernetes tools and technologies.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• 2-7 year relevant experience.
• Proven experience in AIops, MLOps, or related fields.
• Strong proficiency in Python and experience with FastAPI.
• Strong hands-on expertise on Kubernetes (Or AKS).
• Hands-on experience with MS Azure and its AI/ML services, including Azure ML Flow.
• Proficiency in using DevContainer for development.
• Knowledge of CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps.
• Experience with containerization and orchestration tools like Docker and Kubernetes.
• Strong problem-solving skills and the ability to work in a fast-paced environment.
• Excellent communication and collaboration skills.

Preferred Skills

• Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Familiarity with data engineering tools like Apache Kafka, Apache Spark, or similar.
• Knowledge of monitoring and logging tools such as Prometheus, Grafana, or ELK stack.
• Understanding of data versioning tools like DVC or MLflow.
• Experience with infrastructure as code (IaC) tools like Terraform or Ansible.
• Proficiency in Azure-specific tools and services, such as: Azure Machine Learning (Azure ML), Azure DevOps, Azure Kubernetes Service (AKS), Azure Functions, Azure Logic Apps, Azure Data Factory, Azure Monitor and Application Insights.