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Wockhardt logo — Wockhardt Graph Machine Learning Intern in Navi Mumbai, Maharashtra
Wockhardt VerifiedActively Hiring

Graph Machine Learning Intern

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Location

Navi Mumbai, Maharashtra

Work Mode

Hybrid

Duration

2 months

Stipend

₹36,000/mo

Start Date

Immediate / Rolling

Openings

7 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹36,000/moApply on Company Website ↗

About the Internship

Wockhardt is hiring a Graph Machine Learning Intern in Navi Mumbai — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to graph machine learning and network analysis rather than a certificate-only programme. About the role As a Graph Machine Learning…

About Wockhardt

Wockhardt offers a mentor-led Graph Machine Learning Intern in Navi Mumbai with live project work in machine learning, a stipend of ₹36,000/month and a Pre-Placement Offer opportunity for strong performers.
Navi Mumbai, MaharashtraVerified employer7 openings
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Skills Required

Graph Neural NetworksNetworkX / PyTorch GeometricPythonGraph Databases (Neo4j)Node & Edge FeaturesLink PredictionCommunity DetectionSQLData ModellingVisualisation

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), M.Tech, MCA or M.Sc (CS / Mathematics) who are based in or willing to work from Navi Mumbai. You should be keen to learn Graph Neural Networks, NetworkX / PyTorch Geometric, 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

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

Interview & Selection Process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Online aptitude / domain assessment
36,000/month

Stipend · 2 months

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Openings7 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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