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Pocket FM logo — Pocket FM Deep Learning Intern in Hapur, Uttar Pradesh
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Deep Learning Intern

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Location

Hapur, Uttar Pradesh

Work Mode

Work from Home

Duration

2 months

Stipend

₹18,000/mo

Start Date

Immediate / Rolling

Openings

15 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹18,000/moApply on Company Website ↗

About the Internship

Pocket FM has an open Deep Learning Intern position in Hapur for motivated freshers and final-year students. You will work on live deep learning projects and finish with something you can genuinely talk about in interviews. About the role As a Deep Learning Intern at Pocket FM, your core focus…

About Pocket FM

Pocket FM offers a mentor-led Deep Learning Intern in Hapur with live project work in machine learning, a stipend of ₹18,000/month and a Pre-Placement Offer opportunity for strong performers.
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Hapur, Uttar PradeshVerified employer15 openings
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Skills Required

PythonPyTorchTensorFlowNeural NetworksCNNs & RNNsBackpropagationGPU TrainingRegularisationModel EvaluationGit

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT/ECE), BCA/MCA or B.Sc/M.Sc (Computer Science / IT) who are based in or willing to work from Hapur. You should be keen to learn Python, PyTorch, TensorFlow 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

Networking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentorLive project experienceDirect access to the team that owns the data you work on

Interview & Selection Process

4 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. 3Practical assignment or case study with a short walkthrough
  4. 4HR discussion — stipend, start date, expectations and offer
18,000/month

Stipend · 2 months

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Openings15 positions
Applicants0 applied
ModeWork from Home
CategoryMachine Learning
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