Time since we first saw it
Day 193
Up longer than most. Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
Machine Learning Intern
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- New graduates
- For current students
Job title: Machine Learning Intern
What you’ll work on
Full postingBuild and prototype LLM-backed features with senior engineers
Ship a meaningful slice of an LLM feature into production
Contribute to eval rubrics, test plans and quality dashboards
Write clean, testable Python and add regression tests
Debug failures across data, infra, model and prompt logic
From the employer’s posting
Build and prototype LLM-backed features alongside senior engineers
ship a meaningful slice of one into production by the end of the internship
Contribute to eval rubrics, test plans, and quality dashboards
Write clean, testable Python in our production stack, add tests that catch regressions
Debug failures across data, infra, model, and prompt logic with your mentor
Benefits in the posting
Full benefits wording- Competitive internship stipend.
- Rewarding Experience: Competitive stipend and standout career credentials.
From the employer’s posting.
About Enterpret
Our mission: to unlock the voice of the customer for every product team on the planet.
In the employer’s words · Read in context
Posting record
Report an errorOpen 6 monthsWe first saw this posting 193 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- May 4, 2026193 days ago
- Recorded sightings
- 24
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Enterpret is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
Where the posting names them
- 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.
- 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.
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bengaluru
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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.