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Bugcrowd logo — Bugcrowd ML Platform Engineer Intern in Agra, Uttar Pradesh
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ML Platform Engineer Intern

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Location

Agra, Uttar Pradesh

Work Mode

Hybrid

Duration

6 months

Stipend

₹22,000/mo

Start Date

Immediate / Rolling

Openings

9 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹22,000/moApply on Company Website ↗

About the Internship

Bugcrowd is hiring a ML Platform Engineer Intern in Agra — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to internal machine learning platforms rather than a certificate-only programme. About the role As a ML Platform Engineer Intern at Bugcrowd…

About Bugcrowd

Bugcrowd offers a mentor-led ML Platform Engineer Intern in Agra with live project work in machine learning, a stipend of ₹22,000/month and a Pre-Placement Offer opportunity for strong performers.
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Agra, Uttar PradeshVerified employer9 openings
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Skills Required

PythonDocker & KubernetesCI/CDCloud (AWS / Azure / GCP)Experiment TrackingPipeline OrchestrationAPI DesignMonitoringInfrastructure as CodeDeveloper Experience

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (CSE/IT), MCA or M.Sc (Computer Science) who are based in or willing to work from Agra. You should be keen to learn Python, Docker & Kubernetes, CI/CD 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

4 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Technical interview on fundamentals and your projects
  3. 3Practical assignment or case study with a short walkthrough
  4. 4HR discussion — stipend, start date, expectations and offer
22,000/month

Stipend · 6 months

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Openings9 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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