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Open nowPosted 184 days ago

Machine Learning Intern

Enterpret17 open roles

Where
Bengaluru
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Your applicationOpen nowMachine Learning InternEnterpret · Bengaluru

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted 184 days ago

The posting

About Us

Enterpret is redefining how businesses understand and act on customer feedback. We are building an AI-native platform that centralises feedback from every source surveys, reviews, support tickets, communities and turns it into clear, actionable insights that drive business growth.

We are trusted by some of the world’s most customer-obsessed companies like Canva, Descript, Notion, Perplexity and many more, and backed by leading investors like Kleiner Perkins, Canaan Partners, and Peak XV Partners. Our mission: to unlock the voice of the customer for every product team on the planet.

What You’ll Do ?

At Enterpret, our internship program isn’t about side projects, it’s a launchpad for future team members. You’ll work on problems as deep and complex as you can handle, directly impacting the systems our customers rely on.

As a Machine Learning Intern, you will:

  • Build and prototype LLM-backed features alongside senior engineers — retrieval pipelines, agents, evaluation harnesses, or hybrid patterns — and ship a meaningful slice of one into production by the end of the internship.
  • Contribute to eval rubrics, test plans, and quality dashboards that make AI feature quality measurable, and run evals on shipped systems.
  • Write clean, testable Python in our production stack, add tests that catch regressions, and help monitor and harden systems already in production.
  • Debug failures across data, infra, model, and prompt logic with your mentor, and write up what you learn so the team learns with you.
  • Collaborate with engineers, product, and the AI team — joining design reviews, shipping PRs, and participating in design decisions on features you contribute to.
  • Continuously raise the bar on your own craft: ask sharp questions in code reviews, read the systems before you change them, and push for quality without being asked.

What It Takes?

  • Demonstrated AI/ML project depth — coursework, research, open-source, hackathons, or prior internships where you've built something non-trivial with LLMs and evaluated it rigorously.
  • At least one substantial project where you owned a system end-to-end — designed it, built it, and dealt with what broke. Tenure of effort matters more than tenure of employment.
  • Solid engineering skills in Python: you write clean, testable code, debug at system boundaries, and are comfortable in production-style stacks.
  • Working knowledge of modern LLMs — prompting, fine-tuning, retrieval, agents, or evaluation. You've gone deeper than a tutorial on at least one of these.
  • A systems mindset: you think in interfaces, data contracts, failure modes, and rollout plans — not just model tweaks.
  • A track record of collaborating and learning in the open — asking sharp questions, giving and taking feedback, and pushing for quality without being asked.
  • Available to work full-time onsite in Bengaluru for the internship duration, with intent to convert to a full-time role.

What You’ll Gain ?

  • Mentorship from engineers who have scaled AI-native systems.
  • Exposure to cutting-edge tech
  • Understanding of real-world product development in a high-growth AI-driven startup.
  • Potential Pre-Placement Offer (PPO) based on your performance.

Perks

  • Competitive internship stipend.
  • Learning & development resources in AI technologies.
  • Autonomy and ownership from day one.

Why Enterpret ?

  • Real Impact: Contribute to production features used by top global companies.
  • Fast Learning: Work on AI, data, and scalable systems from day one.
  • Mentorship: Learn directly from experienced engineers and product leaders.
  • Big Problems: Solve challenges at the intersection of AI, data, and infrastructure.
  • Startup Exposure: Be part of design, architecture, and product discussions.
  • Builder Culture: Autonomy to experiment, innovate, and grow.
  • Rewarding Experience: Competitive stipend and standout career credentials.
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