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Pocketly logo — Pocketly ML Platform Engineer Intern in Amritsar, Punjab
Pocketly VerifiedActively Hiring

ML Platform Engineer Intern

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Location

Amritsar, Punjab

Work Mode

Work from Home

Duration

3 months

Stipend

₹24,000/mo

Start Date

Immediate / Rolling

Openings

3 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹24,000/moApply on Company Website ↗

About the Internship

Pocketly has an open ML Platform Engineer Intern position in Amritsar for motivated freshers and final-year students. You will work on live internal machine learning platforms projects and finish with something you can genuinely talk about in interviews. About the role As a ML Platform Engineer…

About Pocketly

Pocketly offers a mentor-led ML Platform Engineer Intern in Amritsar with live project work in machine learning, a stipend of ₹24,000/month and a Pre-Placement Offer opportunity for strong performers.
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Amritsar, PunjabVerified employer3 openings
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Skills Required

PythonDocker & KubernetesCI/CDCloud (AWS / Azure / GCP)Experiment TrackingPipeline OrchestrationAPI DesignMonitoringInfrastructure as CodeDeveloper Experience

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), MCA or M.Sc (Computer Science) who are based in or willing to work from Amritsar. You should be keen to learn Python, Docker & Kubernetes, CI/CD 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

Live project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionals

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
24,000/month

Stipend · 3 months

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Openings3 positions
Applicants0 applied
ModeWork from Home
CategoryMachine Learning
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