ML Ops Engineer- Intern at Aaizel International Technologies Pvt Ltd · gurugram · 0 - 1 years · ₹10000 - ₹15000 / mo · Raised funding · Posted 7 Jul 2026

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 ResponsibilitiesMLOps
- 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

About Aaizel International Technologies Pvt Ltd
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Educational Qualification:• B.Tech / M. Tech / M.S. in Computer Science, Data Engineering, AI or related discipline.• Certification in cloud DevOps or MLOps platforms (AWS DevOps Engineer, AzureDevOps Expert, GCP Professional ML Engineer) is highly desirable.• Contributions to MI-Ops or DevOps open source projects is preferred
Experience:• 7—10 years in machine learning operations or DevOps engineering.• Minimum 4 years building CVCD pipelines for AI/ML model deployment in enterprise orgovernment ecosystems.• Proven experience with containerized and microservice architectures.
Key Responsibilities:1.Design and manage continuous integration and delivery (CVCD) pipelines for AIIMLmodels across multiple environments.2. Establish model versioning, deployment, monitoring, and rollback mechanisms to ensurestability and traceability.3.Automate training, testing, and serving workflows using containerized solutions.4.Define infrastructure-as-code templates for scalable AI deployment on on-prem or cloud environments.5. Collaborate with Data Science and Engineering teams to standardize model input/outputformats and performance metrics.6.Implement logging, monitoring, and alerting for deployed models to ensure highavailability and accuracy over time.7.Ensure compliance with Responsible Al guidelines for deployment, including bias auditingand explainability tracking.
- Technical Competencies:• MLOps Platforms: MLflow, Kubeflow, Azure ML, AWS SageMaker Pipelines, GCP VertexAl Pipelines for end-to—end ML workflow orchestration• Containerization: Docker, Kubernetes, Helm charts, container registries, and microservicesarchitecture for ML workloads• CI/CD: Jenkins, GitLab CI, GitHub Actions, Azure DevOps with specialized ML pipelineintegration and automated testing• Infrastructure-as-Code: Terraform, CloudFormation, Ansible for reproducible MLinfrastructure provisioning and management• Cloud Platforms: AWS (EKS, Lambda, ECR, S3), Azure (AKS, Container Registry, BlobStorage), GCP (GKE, Cloud Build, Cloud Storage)• Model Serving: TorchServe, TensorFlow Serving, Seldon, KServe, REST APIs, and real-time inference infrastructure.• Programming Languages: Python for automation, Bash scripting, YAML for configurationmanagement, basic understanding Of Go/Java• Database & Storage: Feature stores (Feast, Tecton), model registries, data versioning(DVC), and distributed storage systems• Workflow Orchestration: Apache Airflow, Prefect, Argo Workflows for complex MLpipeline scheduling and dependency management.
About the Internship
SkillSecure X is looking for motivated DevOps with AI Interns who are interested in cloud technologies, automation, CI/CD, containerization, and AI-powered DevOps practices. This internship provides hands-on experience through real-world projects and guided mentorship.
Responsibilities
- Assist in building and maintaining CI/CD pipelines.
- Learn and work with Docker, Git, and cloud platforms.
- Support deployment automation and infrastructure management.
- Explore AI tools to improve DevOps workflows and monitoring.
- Monitor application performance and troubleshoot basic issues.
- Complete weekly assignments and document project progress.
Required Skills
- Basic knowledge of Linux and Git.
- Understanding of DevOps concepts and software development lifecycle.
- Familiarity with cloud platforms (AWS, Azure, or Google Cloud) is a plus.
- Basic scripting knowledge (Python, Bash, or Shell).
- Strong problem-solving and analytical skills.
Eligibility
- Undergraduate or postgraduate students.
- Recent graduates.
- Students pursuing Computer Science, Information Technology, Software Engineering, Cloud Computing, DevOps, or related disciplines.
Benefits
- Hands-on DevOps and AI project experience.
- Mentor-guided learning.
- Internship Completion Certificate.
- Letter of Recommendation (based on performance).
- Portfolio-building opportunities.
- Flexible remote internship.
Greetings!
Hiring For Large Product Based Company!
Role- Mlops Engineer
Experience- 8-12 years
Location- Pune, Nagpur
JD-
- 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering
- Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure
Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn
- Bachelor’s degree in computer science, Data Science, Information Systems, or a related field
- 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering
- Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure
- Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn
About the Internship
SkillSecure X is seeking passionate Artificial Intelligence & Machine Learning (AI/ML) Interns who are eager to develop practical skills in machine learning, deep learning, and AI applications. Interns will work on guided projects, gain hands-on experience with real-world datasets, and learn industry-standard AI tools and techniques.
Responsibilities
- Assist in developing AI and Machine Learning models.
- Work with Python and popular ML libraries.
- Prepare, clean, and analyze datasets.
- Perform data preprocessing and model evaluation.
- Build basic predictive and classification models.
- Document project progress and complete weekly assignments.
Required Skills
- Basic knowledge of Python programming.
- Understanding of Machine Learning fundamentals.
- Familiarity with Data Science concepts.
- Knowledge of libraries such as NumPy, Pandas, or Scikit-learn is a plus.
- Strong analytical and problem-solving skills.
Eligibility
- Undergraduate or postgraduate students.
- Recent graduates.
- Students pursuing Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or related disciplines.
Benefits
- Hands-on AI & ML project experience.
- Mentor-guided learning.
- Internship Completion Certificate.
- Letter of Recommendation (based on performance).
- Portfolio-building opportunities.
- Flexible remote internship.
About PGAGI:
We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.
About the Role
We are at the forefront of building advanced AI systems — from fully autonomous agents that power intelligent customer interactions, to data analysis tools that deliver actionable business insights. This internship combines hands-on AI/ML engineering with robust backend development, giving you a complete picture of how production-grade AI systems are built, deployed, and scaled.
You will work across the full stack: designing and fine-tuning AI models on one end, and architecting the APIs, databases, and server-side infrastructure that bring those models to life on the other.
Key Responsibilities
AI / ML ENGINEERING
Design, experiment with, and fine-tune large language models (LLMs) and NLP pipelines for real-world use cases.
Develop and iterate on prompt engineering strategies to optimise model performance and output quality.
Integrate and deploy models using Hugging Face and OpenAI platforms; evaluate open-source alternatives.
Build deep learning workflows including training, evaluation, and continuous improvement loops.
Collaborate on data collection, preprocessing, and feature engineering for ML pipelines.
BACKEND ENGINEERING
Architect and develop scalable RESTful APIs and GraphQL endpoints using Node.js / FastAPI / Express.
Build and maintain full-stack features using Next.js (App Router), integrating server-side rendering, API routes, and React components.
Design and manage relational and NoSQL databases (PostgreSQL, MongoDB, or equivalent); write efficient queries and manage schema migrations.
Implement authentication, authorisation, and security best practices (JWT, OAuth 2.0, role-based access control).
Containerise services with Docker and contribute to CI/CD pipelines for reliable, automated deployments.
Integrate AI/ML model inference endpoints into backend services, handling async processing, queuing, and latency optimisation.
Write clean, well-tested, and well-documented backend code; participate actively in code reviews.
VERSION CONTROL & COLLABORATION
Use Git and GitHub for all version control workflows — branching strategies, pull requests, and code reviews.
Contribute to technical documentation, architecture decision records, and internal knowledge bases.
Duration & Compensation
Duration: 6 Months
Stipend: Base ₹8,000/month — up to ₹15,000/month based on performance
Post-Internship: Full-time opportunity as AI/ML Engineer (₹6–8 LPA) based on performance
Perks & Benefits
Hands-on experience shipping real AI products used by actual customers.
Mentorship from senior engineers and industry experts in AI/ML and backend development.
Exposure to the full development lifecycle — from model training to production deployment.
Collaborative, innovative, and flexible work environment.
Accelerated growth path with a clear route to a full-time engineering role.
How to Apply
Interested candidates are invited to submit their resume and complete the assignment using
the link : https://pgagi.in/jobs/28df1e98-f0c3-4d58-9509-d5b1a4ea9754
Shortlisted candidates will be contacted for an interview.
Selection Process
Initial Screening: We'll review your application for evidence of your skills, experience, and a strong foundation in AI.
Task Assignment: Candidates need to submit assignment which is already being attached in careers page , designed to assess your practical skills.
Performance Review: Our experts will evaluate your task submission, with excellence in this stage being crucial for further consideration.
Interview: Impressive task performers will be invited for an interview to discuss their potential contribution to our team.
Onboarding: Successful candidates will join our team, with exciting projects ahead
Requirements
MUST-HAVE SKILLS
Strong proficiency in Python for AI/ML development and scripting.
Solid understanding of JavaScript / TypeScript; experience with Node.js and Next.js (or a strong willingness to learn quickly).
Familiarity with REST API design principles and at least one backend framework (Express, FastAPI, Django, etc.).
Working knowledge of at least one database system (PostgreSQL, MySQL, MongoDB).
Experience with Git and GitHub version control workflows.
Exposure to AI/ML platforms such as Hugging Face and OpenAI.
Understanding of prompt engineering concepts and the model fine-tuning process.
GOOD TO HAVE
Hands-on experience with Next.js App Router, React Server Components, or similar modern full-stack frameworks.
Familiarity with Docker, basic DevOps concepts, or cloud platforms (AWS, GCP, or Azure).
Experience with message queues (Redis, RabbitMQ) or background task processing.
Knowledge of LLM orchestration tools such as LangChain or LlamaIndex.
SOFT SKILLS & MINDSET
Strong problem-solving instincts and a genuine curiosity about AI technology.
Ability to own tasks end-to-end and communicate progress clearly.
Comfortable working in a fast-moving environment where requirements evolve.
A growth mindset — eager to learn, receive feedback, and level up continuously.
TECH YOU'LL WORK WITH
Python
Next.js
Node.js
FastAPI
LLMs / NLP
PostgreSQL
React
Docker
HuggingFace
OpenAI API
GitHub
REST / GraphQL
Apply now to embark on a transformative career journey with PGAGI, where innovation and talent converge!
#artificialintelligence #Machinelearning #AI #AIML #LLM #FastAPI #NLP #openAI #AImodels #AIMLInternship #AIintern #Internship #aimlgraduate #Python
About Us
Corporate Web Solutions provides technology and digital transformation solutions with an emphasis on emerging technologies including artificial intelligence and machine learning.
Role Overview
As an AI & Machine Learning Intern, you'll gain practical experience working with datasets, machine learning models, AI concepts, and Python-based tools.
Key Responsibilities
- Prepare and analyze datasets.
- Assist in developing machine learning models.
- Experiment with AI and ML algorithms.
- Evaluate model performance.
- Work with Python and relevant libraries.
- Participate in practical AI/ML projects.
Requirements
- Basic Python programming knowledge.
- Understanding of machine learning fundamentals.
- Basic knowledge of data handling.
- Familiarity with NumPy and Pandas is a plus.
- Eagerness to learn AI technologies.
Perks
- Certificate of Internship
- Flexible work hours
- Mentorship and real project exposure
- Potential for PPO
- Letter of Recommendation
- Performance-Based Stipend available up to ₹18,000/month
About Us
Corporate Web Solutions works with modern development and digital transformation technologies, providing interns with practical exposure to software development and deployment workflows.
Role Overview
As a DevOps Intern, you'll gain hands-on exposure to deployment, automation, version control, CI/CD, and cloud technologies.
Key Responsibilities
- Assist with application deployment.
- Work with Git and version control.
- Learn CI/CD workflows.
- Assist with development automation.
- Explore cloud and DevOps tools.
- Monitor and troubleshoot development environments
.
Requirements
- Basic understanding of software development.
- Familiarity with Git/GitHub.
- Basic Linux knowledge is a plus.
- Interest in cloud and DevOps technologies.
- Willingness to learn.
Perks
- Certificate of Internship
- Flexible work hours
- Mentorship and real project exposure
- Potential for PPO
- Letter of Recommendation
- Performance-Based Stipend available up to ₹18,000/month
Job Title: Java AWS Kubernetes DevOps AI/ML
Experience: 8–10 Years
The candidate should have at least 1 year of experience in AI/ML and hands-on experience with the below technologies:
Java
AWS
Kubernetes
DevOps
AI/ML
MongoDB / PostgreSQL
Key-Value Caching
Vector Databases – ChromaDB / Pgvector
Company Overview:
Planview is hiring a DevOps Engineer in Bengaluru, India to support Planview SaaS applications across the product line. You will work in a global, collaborative team — owning CI/CD pipelines, cloud infrastructure, and automation to keep deployments fast and systems reliable.
Responsibilities
- Build and maintain CI/CD pipelines in Jenkins for reliable, fast delivery.
- Manage containerized workloads on Docker and ECS — task definitions, services, and clusters.
- Provision and manage AWS infrastructure using Terraform (CloudFormation a plus).
- Automate configuration and deployment tasks using Python (Ansible a plus).
- Set up and maintain monitoring and alerting via New Relic (CloudWatch, Datadog, or Prometheus/Grafana a plus).
- Write Shell and Python scripts to automate operations and reduce manual work.
- Manage Git workflows — branching, merge strategies, and pull request reviews.
- Administer and support MSSQL databases underpinning the product line — backups, restores, and basic performance troubleshooting.
- Troubleshoot deployment, performance, and infrastructure issues with development teams.
- Participate in on-call rotations and drive incident response.
- Continuously improve infrastructure resilience and deployment speed.
- Apply AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) to speed up IaC authoring, pipeline debugging, and day-to-day scripting.
Qualifications
Must-Have Skills
- Experience: 4–6 years of experience in DevOps, SRE, or Infrastructure Engineering.
- OS: Windows administration (systemd, package management, log analysis).
- Cloud: AWS (Active Directory, ECS, EC2, CloudFront, S3, VPC, IAM, RDS, Lambda basics).
- Source Control: Git — branching, merge/rebase, PR reviews.
- CI/CD (Jenkins): Pipeline creation and basic Groovy scripting.
- Containerization (Docker + ECS): Task definitions, services, and clusters.
- IaC: Terraform.
- Monitoring: New Relic.
- Scripting: Bash and Python scripting for automation.
- Networking Basics: DNS, load balancers, security groups, VPNs.
- Logging: ELK stack / CloudWatch Logs.
- Database: MSSQL administration — backups, restores, basic performance troubleshooting.
- Infrastructure Automation: Hands-on experience automating infrastructure provisioning, configuration, and deployment end-to-end.
- AI-Assisted Engineering: Comfortable working with AI coding/DevOps assistants (e.g., GitHub Copilot, Claude Code) for IaC generation, scripting, and troubleshooting — verified via a mandatory AI proficiency assessment during interviews.
Nice-to-Have Skills
• Configuration Management: Ansible.
• Additional IaC: CloudFormation.
• Architecture: Knowledge of microservices architecture.
• Cloudflare: DNS, CDN, WAF.
• Artifact Repositories: Nexus, JFrog Artifactory, ECR.
• Other CI/CD Tools: GitHub Actions.
• AWS cost optimization / FinOps awareness.
• Datadog, CloudWatch, or Prometheus/Grafana.
• AIOps: Exposure to AI-driven anomaly detection, root-cause analysis, or incident triage (e.g., Dynatrace Davis AI, Datadog Bits AI, Harness AIDA).
• Database Basics: RDS backups, restores, performance tuning.










