Jar

MLOps Engineer Intern

InternshipHybridVijayawada, Andhra Pradesh6 months41K/mo3 openingsImmediate / Rolling

About this internship

Join Jar in Vijayawada as a MLOps Engineer Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on ML platform and operations work. About the role As a MLOps Engineer Intern at Jar, your core focus will be…

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Skills you'll use

KubeflowMLflowCI/CD for AIDocker / KubernetesModel Monitoring & Drift DetectionPythonFeature StoresModel Registry & VersioningCloud ML PlatformsInfrastructure as Code

What you'll do

Work on building the pipelines that get models retrained, deployed and watched alongside the core team
Apply Kubeflow, MLflow, CI/CD for AI, Docker / Kubernetes to live, production-facing problems
Document your work clearly for reviewers and stakeholders
Participate in reviews and act on the feedback you receive
Collaborate across engineering, product, design or business as required
Follow the team's quality, testing and documentation standards

Who can apply

Pursuing or recently completed B.E./B.Tech (CSE/IT), MCA or M.Sc (Computer Science / Data Science) — 2026 freshers & final-year students welcome
Working knowledge of Kubeflow, MLflow, CI/CD for AI (or a genuine willingness to learn them)
Strong fundamentals in your discipline and clear problem-solving ability
Care with detail and the discipline to document your work
Clear written and verbal communication in English
Based in or willing to work from Vijayawada, Andhra Pradesh

Perks & benefits

Mentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hours

Interview & selection process

2 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Online aptitude / domain assessment

About Jar

Jar operates in the savings & investment sector and has an active presence in Vijayawada. Interns here are put on real work from the start, because the team's view is that the fastest way to learn a craft is to practise it under people who already do it well — not to watch it from a distance. The…

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