MLOps Engineer Intern

Job Description

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 roleAs a MLOps Engineer Intern at Jar, your core focus will be building the pipelines that get models retrained, deployed and watched. You are attached to a named mentor, join the teams stand-ups and reviews, and are trusted with work that matters rather than filler tasks. Questions are encouraged, your output is reviewed properly, and you get the feedback you need to actually improve.What youll do day to day Work on building the pipelines that get models retrained, deployed and watched alongside the core team Use Kubeflow, MLflow, CI/CD for AI, Docker / Kubernetes, Model Monitoring & Drift Detection on live, production-facing problems Turn your work into clear documentation, notes or decks for reviewers Take part in reviews and act on the feedback you receive Collaborate across functions engineering, product, design or business as the work demands Follow the teams quality, testing and documentation standards Track and report your own progress against an agreed planSkills youll buildYou will build practical, demonstrable experience in Kubeflow, MLflow, CI/CD for AI, Docker / Kubernetes, Model Monitoring & Drift Detection, Python, Feature Stores, Model Registry & Versioning, Cloud ML Platforms, Infrastructure as Code the exact toolkit that separates a hireable fresher from a CV full of coursework. No prior work experience is required. Curiosity, problem-solving ability and a willingness to learn matter far more here than a polished rsum, and every one of these skills is taught on the job.Who should applyStudents in their final year or recent graduates from B.E./B.Tech (CSE/IT), MCA or M.Sc (Computer Science / Data Science) based in or willing to work from Vijayawada. You should be willing to learn Kubeflow, MLflow, CI/CD for AI and able to communicate clearly in writing. Personal projects, coursework, certifications or open-source contributions strengthen your application, but none of them are mandatory.Internship detailsThis is a 6-month internship in Vijayawada, Andhra Pradesh, with a stipend of 41,000 per month. You will be given a defined project so that you leave with an automated retrain-and-deploy pipeline with drift alerts. Working hours follow the teams normal business hours and the internship includes a certificate on successful completion.By the end of the internship you will have hands-on command of the tools and workflows used in the field, plus the confidence that comes from solving genuine problems rather than textbook ones. Interns who excel are regularly offered a PPO and a path into a full-time position.How to applyClick Apply Now. If you are not logged in you will be asked to sign in and register first, after which you will be taken to Jars official careers page to complete your application. Applications are reviewed on a rolling basis and seats are limited, so apply early. Responsibilities: 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 teams quality, testing and documentation standards. Requirements: 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. .

Keyskills :
DockerKubernetesPythonKubeflowMLflowCICD for AIModel MonitoringDrift DetectionFeature Stores