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CarWale logo — CarWale NLP Engineering Intern in Navi Mumbai, Maharashtra
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NLP Engineering Intern

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Location

Navi Mumbai, Maharashtra

Work Mode

Hybrid

Duration

3 months

Stipend

₹26,000/mo

Start Date

Immediate / Rolling

Openings

7 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹26,000/moApply on Company Website ↗

About the Internship

CarWale is hiring a NLP Engineering Intern in Navi Mumbai — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to natural language processing rather than a certificate-only programme. About the role As a NLP Engineering Intern at CarWale, your core focus…

About CarWale

CarWale offers a mentor-led NLP Engineering Intern in Navi Mumbai with live project work in machine learning, a stipend of ₹26,000/month and a Pre-Placement Offer opportunity for strong performers.
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Navi Mumbai, MaharashtraVerified employer7 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 Navi Mumbai. 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

Exposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship Certificate

Interview & Selection Process

3 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. 3HR discussion — stipend, start date, expectations and offer
26,000/month

Stipend · 3 months

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Openings7 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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