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DataNimbus logo — DataNimbus NLP Engineering Intern in Pune, Maharashtra
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NLP Engineering Intern

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Location

Pune, Maharashtra

Work Mode

Hybrid

Duration

3 months

Stipend

₹24,000/mo

Start Date

Immediate / Rolling

Openings

5 positions

Type

Full-time

Category

Machine Learning

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

About the Internship

Join DataNimbus in Pune as a NLP Engineering Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on natural language processing work. About the role As a NLP Engineering Intern at DataNimbus, your core…

About DataNimbus

DataNimbus offers a mentor-led NLP Engineering Intern in Pune 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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Pune, MaharashtraVerified employer5 openings
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Skills Required

PythonHugging Face TransformersPyTorchTokenisationText ClassificationNamed Entity RecognitionEmbeddingsModel EvaluationPandasGit

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (any branch), B.Sc/M.Sc (Statistics, Mathematics, Economics), BCA/MCA or MBA who are based in or willing to work from Pune. You should be keen to learn Python, Hugging Face Transformers, PyTorch 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

Flexible working hoursNetworking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentor

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
24,000/month

Stipend · 3 months

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Openings5 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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