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Neo Wealth and Asset Management logo — Neo Wealth and Asset Management Machine Learning Engineer Intern in Dhule, Maharashtra
Neo Wealth and Asset Management VerifiedActively Hiring

Machine Learning Engineer Intern

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Location

Dhule, Maharashtra

Work Mode

Hybrid

Duration

6 months

Stipend

₹30,000/mo

Start Date

Immediate / Rolling

Openings

4 positions

Type

Full-time

Category

Machine Learning

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About the Internship

Join Neo Wealth and Asset Management in Dhule as a Machine Learning Engineer Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on applied machine learning and model deployment work. About the role As a…

About Neo Wealth and Asset Management

Neo Wealth and Asset Management offers a mentor-led Machine Learning Engineer Intern in Dhule with live project work in machine learning, a stipend of ₹30,000/month and a Pre-Placement Offer opportunity for strong performers.
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Dhule, MaharashtraVerified employer4 openings
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Skills Required

PythonTensorFlowScikit-LearnModel Deployment (MLOps)Feature EngineeringPandas & NumPyModel Evaluation MetricsDockerREST / gRPC Model ServingExperiment Tracking (MLflow)

Who Can Apply

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

Mentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hours

Interview & Selection Process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Technical interview on fundamentals and your projects
30,000/month

Stipend · 6 months

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Openings4 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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