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American Express logo — American Express AI/ML Engineering Intern in Aurangabad, Maharashtra
American Express VerifiedActively Hiring

AI/ML Engineering Intern

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Location

Aurangabad, Maharashtra

Work Mode

Hybrid

Duration

3 months

Stipend

₹26,000/mo

Start Date

Immediate / Rolling

Openings

2 positions

Type

Full-time

Category

Machine Learning

Apply Now — ₹26,000/moApply on Company Website ↗

About the Internship

Join American Express in Aurangabad as a AI/ML Engineering Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on AI engineering work. About the role As a AI/ML Engineering Intern at American Express, your…

About American Express

American Express offers a mentor-led AI/ML Engineering Intern in Aurangabad with live project work in machine learning, a stipend of ₹26,000/month and a Pre-Placement Offer opportunity for strong performers.
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Aurangabad, MaharashtraVerified employer2 openings
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Skills Required

PythonFastAPIREST APIsLLM IntegrationDockerModel DeploymentCloud PlatformsGitPrompt EngineeringTesting

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech/BCA/MCA/M.Sc (CS, AI) who are based in or willing to work from Aurangabad. You should be keen to learn Python, FastAPI, REST APIs 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

4 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Discussion with the hiring manager on the role and your fit
  3. 3Team-fit / behavioural interview with the team
  4. 4HR discussion — stipend, start date, expectations and offer
26,000/month

Stipend · 3 months

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Openings2 positions
Applicants0 applied
ModeHybrid
CategoryMachine Learning
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