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LatentView Analytics

MLOps Intern

InternshipHybridJammu, Jammu & Kashmir2 months34K/mo1 openingImmediate / Rolling

About this internship

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

Skills you'll use

PythonDockerKubernetesMLflowCI/CDModel MonitoringAWS / GCPAirflowGitLinux

What you'll do

  • Work on packaging, deploying and monitoring models in production alongside the core team
  • Apply Python, Docker, Kubernetes, MLflow 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/BCA/MCA — 2026 freshers & final-year students welcome
  • Working knowledge of Python, Docker, Kubernetes (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 Jammu, Jammu & Kashmir

Perks & benefits

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

Interview & selection process

3 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Technical interview on fundamentals and your projects
  3. 3HR discussion — stipend, start date, expectations and offer

About LatentView Analytics

LatentView Analytics operates in the analytics consulting sector and has an active presence in Jammu. 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…
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