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McKinsey & Company logo — McKinsey & Company Machine Learning Engineer Intern in Vasco da Gama, Goa
McKinsey & Company VerifiedActively Hiring

Machine Learning Engineer Intern

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Location

Vasco da Gama, Goa

Work Mode

In Office

Duration

3 months

Stipend

₹36,000/mo

Start Date

Immediate / Rolling

Openings

2 positions

Type

Full-time

Category

Machine Learning

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

About the Internship

McKinsey & Company is hiring a Machine Learning Engineer Intern in Vasco da Gama — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to applied machine learning and model deployment rather than a certificate-only programme. About the role As a Machine…

About McKinsey & Company

McKinsey & Company offers a mentor-led Machine Learning Engineer Intern in Vasco da Gama with live project work in machine learning, a stipend of ₹36,000/month and a Pre-Placement Offer opportunity for strong performers.
Vasco da Gama, GoaVerified employer2 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 Vasco da Gama. 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

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. 2Practical assignment or case study with a short walkthrough
36,000/month

Stipend · 3 months

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Openings2 positions
Applicants0 applied
ModeIn Office
CategoryMachine Learning
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