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Zscaler logo — Zscaler MLOps Engineer Intern in Pune, Maharashtra
Zscaler VerifiedActively Hiring

MLOps Engineer Intern

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Location

Pune, Maharashtra

Work Mode

Hybrid

Duration

4 months

Stipend

₹49,000/mo

Start Date

Immediate / Rolling

Openings

1 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹49,000/moApply on Company Website ↗

About the Internship

Zscaler is hiring a MLOps Engineer Intern in Pune — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to ML platform and operations rather than a certificate-only programme. About the role As a MLOps Engineer Intern at Zscaler, your core focus will be…

About Zscaler

Zscaler offers a mentor-led MLOps Engineer Intern in Pune with live project work in machine learning, a stipend of ₹49,000/month and a Pre-Placement Offer opportunity for strong performers.
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Pune, MaharashtraVerified employer1 opening
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Skills Required

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

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), MCA or M.Sc (Computer Science / Data Science) who are based in or willing to work from Pune. You should be keen to learn Kubeflow, MLflow, CI/CD for AI 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
49,000/month

Stipend · 4 months

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Openings1 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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