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33Brew logo — 33Brew MLOps Engineering Intern in Ranchi, Jharkhand
33Brew VerifiedActively Hiring

MLOps Engineering Intern

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Location

Ranchi, Jharkhand

Work Mode

In Office

Duration

3 months

Stipend

₹20,000/mo

Start Date

Immediate / Rolling

Openings

5 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹20,000/moApply on Company Website ↗

About the Internship

33Brew is hiring a MLOps Engineering Intern in Ranchi — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to MLOps and model infrastructure rather than a certificate-only programme. About the role As a MLOps Engineering Intern at 33Brew, your core focus…

About 33Brew

33Brew offers a mentor-led MLOps Engineering Intern in Ranchi with live project work in machine learning, a stipend of ₹20,000/month and a Pre-Placement Offer opportunity for strong performers.
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Ranchi, JharkhandVerified employer5 openings
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Skills Required

PythonDockerMLflowCI/CDKubernetes BasicsModel Serving APIsData VersioningMonitoring & Drift DetectionAWS or GCPGit

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT/ECE), BCA/MCA or B.Sc (Computer Science / IT) who are based in or willing to work from Ranchi. You should be keen to learn Python, Docker, MLflow on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.

Perks

Internship CertificateLetter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflows

Interview & Selection Process

4 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Practical assignment or case study with a short walkthrough
  3. 3Discussion with the hiring manager on the role and your fit
  4. 4HR discussion — stipend, start date, expectations and offer
20,000/month

Stipend · 3 months

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Openings5 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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