POSTED 14 SEPTEMBER 20262 weeks ago

Amazon ML Challenge 2026

at AmazonOnline / Remote
INTERNSHIPPrizes worth ₹2,25,000 + Pre-Placement InterviewsStudent (2027 / 2028 batch)Online / Remote (REMOTE)🎓 2027 / 2028 Batch📜 PhD / M.E. / M.Tech / M.S. / MS by Research / B.E. / B.Tech (full-time)
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JOB DETAILS & SPECIFICATIONS

ABOUT THE COMPANY

Amazon is a multinational technology giant focused on e-commerce, cloud computing (AWS), digital streaming, and artificial intelligence. It is one of the world’s leading companies in applying machine learning at scale across retail, logistics, and cloud services.

ROLE SUMMARY

Amazon ML Challenge 2026 is a two-stage national competition for engineering students. Participants work on Amazon’s real-world dataset to solve a machine learning problem statement, with the chance to win cash prizes, certificates, and pre-placement interview opportunities with Amazon.

KEY RESPONSIBILITIES

  • Form a team of 3–4 members and register with a valid AWS Builder Center Profile ID
  • Participate in a 72-hour ML Hackathon: receive problem statement & dataset, build solution, and submit code + 1-2 page approach document
  • Compete on the live leaderboard and private leaderboard
  • Top 10 teams present solutions to Amazon Scientists in the virtual Grand Finale
  • Demonstrate innovative ML approaches on real Amazon data

SKILLS REQUIRED

  • Strong foundation in Machine Learning concepts
  • Ability to work with datasets, build and evaluate models
  • Proficiency in Python and common ML libraries
  • Problem-solving and analytical thinking
  • Effective teamwork and documentation skills
  • Willingness to work under time constraints in a hackathon format

ELIGIBILITY

  • Open to students pursuing full-time PhD / M.E. / M.Tech / M.S. / MS by Research / B.E. / B.Tech across engineering campuses in India
  • Graduation Year: 2027 or 2028
  • Team size: 3–4 members (cross-college teams allowed)
  • One student can be part of only one team
  • Registration open; 72-hour hackathon and Grand Finale scheduled in September–October 2026
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Skills to bring

Machine LearningData SciencePythonProblem SolvingTeam CollaborationModel Building

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