ML Ops Engineer- Intern

Aaizel International Technologies Pvt Ltd; Gurugram District; On-site; INR 223,200 - 390,600; Part time

Job summary

Aaizel International Technologies Pvt. Ltd. in Gurugram, Haryana, invites applications for an MLOps Engineer Intern to join our AI/ML infrastructure team.

You will help build, deploy, and maintain production-grade ML pipelines and cloud infrastructure as part of a hands-on internship. The role focuses on containerization, Kubernetes, CI/CD automation, model deployment, monitoring, and cloud-native tech, with mentorship from senior engineers.

Qualifications

• Good understanding of Linux, shell scripting, and networking fundamentals.
• Basic knowledge of Python programming.
• Familiarity with Docker and Kubernetes.
• Understanding of Git and CI/CD concepts.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Basic understanding of machine learning workflows and model deployment.
• Familiarity with REST APIs using Flask, FastAPI, or Django.
• Strong analytical, debugging, and problem-solving skills.
• Good communication and willingness to learn new technologies.

Responsibilities

• Assist in building and maintaining end-to-end ML pipelines using Airflow, Kubeflow Pipelines, or Metaflow.
• Collaborate with AI/ML engineers to deploy ML models using TensorFlow and Airflow orchestration.
• Containerize ML applications using Docker with Flask, FastAPI, or Django APIs.
• Support dataset versioning and experiment tracking using MLflow and DVC.
• Assist in maintaining model registries and reproducible ML workflows.
• Monitor deployed models for performance, data drift, and infrastructure health using Prometheus and Grafana.
• Support automated retraining workflows and model deployment processes.

Skills

Linux

Shell scripting

Python

REST APIs

CI/CD

Cloud platforms

Machine learning workflows

Communication

Education

B.Tech/B.E./M.Tech/MCA eligible

Tools

Docker

Kubernetes

Git

Terraform

Jenkins

Airflow

Kubeflow

Metaflow

MLflow

DVC

Prometheus

Grafana

Job description

About The Job

Job Title: MLOps Engineer Intern

Company: Aaizel International Technologies Pvt. Ltd.

Location: Gurugram, Haryana (On-site)

Duration: 6 Months (PPO based on performance)

About Aaizeltech

Aaizeltech is a deep-tech company building AI/ML-powered platforms, scalable SaaS applications, cybersecurity solutions, and intelligent embedded systems. We are looking for a passionate MLOps Engineer Intern eager to work on real-world machine learning infrastructure, cloud platforms, and deployment pipelines while collaborating with experienced AI/ML engineers.

Role Overview

As an MLOps Engineer Intern, you will assist in building, deploying, and maintaining machine learning pipelines and cloud infrastructure. You will gain hands‑on experience in containerization, Kubernetes, CI/CD automation, model deployment, monitoring, and cloud‑native technologies while contributing to production‑ready AI solutions.

Key Responsibilities - MLOps

• Assist in building and maintaining end‑to‑end ML pipelines using tools such as Airflow, Kubeflow Pipelines, or Metaflow.
• Collaborate with AI/ML engineers to deploy machine learning models using , TensorFlow and Airflow orchestration.
• Containerize ML applications using Docker with Flask, FastAPI, or Django APIs.
• Support dataset versioning and experiment tracking using MLflow and DVC.
• Assist in maintaining model registries and ensuring reproducible ML workflows.
• Monitor deployed models for performance, data drift, and infrastructure health using tools such as Evidently AI, Prometheus, and Grafana.
• Support automated retraining workflows and model deployment processes.

Cloud & DevOps

• Assist in deploying and managing cloud infrastructure on AWS, GCP, or Azure.
• Support CI/CD pipeline development using GitHub Actions, GitLab CI, or Jenkins.
• Learn and contribute to Infrastructure as Code (IaC) using Terraform or CloudFormation.
• Work with Docker and Kubernetes for application deployment and orchestration.
• Monitor cloud resources and optimize infrastructure performance.
• Follow DevOps and DevSecOps best practices for secure deployments.

Required Skills

• Good understanding of Linux, shell scripting, and networking fundamentals.
• Basic knowledge of Python programming.
• Familiarity with Docker and Kubernetes.
• Understanding of Git and CI/CD concepts.
• Knowledge of cloud platforms such as AWS, Azure, or GCP.
• Basic understanding of machine learning workflows and model deployment.
• Familiarity with REST APIs using Flask, FastAPI, or Django.
• Strong analytical, debugging, and problem‑solving skills.
• Good communication and willingness to learn new technologies.

Preferred Skills

• Exposure to MLflow, DVC, Airflow, Kubeflow, or Metaflow, apache kafka.
• Familiarity with Terraform or other Infrastructure as Code tools.
• Knowledge of monitoring tools such as Prometheus or Grafana.
• Understanding of model serving frameworks like BentoML, TorchServe, or TensorFlow Serving.
• Knowledge of DevSecOps tools like SonarQube is an advantage.

Eligibility

• Final‑year B.Tech/B.E./M.Tech/MCA students or recent graduates in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, or related fields.
• Strong interest in MLOps, Cloud Computing, DevOps, and AI infrastructure.
• Prior academic projects, internships, or open‑source contributions in ML or cloud technologies are a plus.

What You’ll Gain

• Hands‑on experience with production‑grade MLOps and cloud infrastructure.
• Opportunity to work on real‑world AI/ML products and scalable deployments.
• Mentorship from experienced AI/ML and DevOps professionals.
• Exposure to modern MLOps tools, Kubernetes, cloud platforms, and CI/CD workflows.
• Potential Pre‑Placement Offer (PPO) based on performance.

Who You’ll Work With

• AI/ML Engineers, Backend Developers, Frontend Developers, QA Team
• Product Owners, Project Managers, and external Government or Enterprise Clients

Skills

• AWS
• Python
• Kubernetes
• Jenkins
• Apache
• CI/CD
• Version Control