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Wiz logo — Wiz NLP Engineer Intern in Pimpri-Chinchwad, Maharashtra
Wiz VerifiedActively Hiring

NLP Engineer Intern

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Location

Pimpri-Chinchwad, Maharashtra

Work Mode

Hybrid

Duration

2 months

Stipend

₹19,000/mo

Start Date

Immediate / Rolling

Openings

14 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹19,000/moApply on Company Website ↗

About the Internship

Wiz is hiring a NLP Engineer Intern in Pimpri-Chinchwad — 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 Engineer Intern at Wiz, your core focus will be…

About Wiz

Wiz offers a mentor-led NLP Engineer Intern in Pimpri-Chinchwad with live project work in machine learning, a stipend of ₹19,000/month and a Pre-Placement Offer opportunity for strong performers.
Pimpri-Chinchwad, MaharashtraVerified employer14 openings
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Skills Required

Natural Language Processing (NLP)Hugging Face TransformersPythonText Preprocessing & TokenisationNamed Entity RecognitionText ClassificationspaCy / NLTKEmbeddingsModel Evaluation (F1)Multilingual Text

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT/AI-ML), MCA, M.Sc (CS / Linguistics) or M.Tech who are based in or willing to work from Pimpri-Chinchwad. You should be keen to learn Natural Language Processing (NLP), Hugging Face Transformers, Python 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

Internship CertificateLetter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflows

Interview & Selection Process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Team-fit / behavioural interview with the team
19,000/month

Stipend · 2 months

Apply Now →
Openings14 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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