Machine Learning (ML) Engineer Intern (Remote)

At a glance

• Company: Peakflo — Y Combinator–backed B2B fintech automating finance operations with AI
• Role: Machine Learning (ML) Engineer Intern
• Location: Remote (India) — fully remote, paid
• Stipend: ≈ ₹40,000 – ₹50,000 / month
• Duration: Flexible; conversion to full-time possible
• Focus: LLMs, NLP, agentic-AI systems, data pipelines

About the role

Peakflo is a Y Combinator–backed B2B fintech that uses AI to automate finance operations for businesses. As a paid, fully-remote ML Engineer Intern, you will help build and ship machine-learning features into a live product — working with large language models (LLMs) and natural-language processing (NLP), building data pipelines, and turning research ideas into production systems.

This is a strong fit for final-year students or recent graduates who have solid Python and a real ML project or two behind them, and who want hands-on experience with modern AI at a fast-growing startup. Because it is fully remote, you can take it from anywhere in India, and conversion to a full-time role is possible based on performance.

What you'll do day to day

• Build and integrate ML / LLM features into Peakflo's product.
• Work with NLP, prompt engineering, and agentic-AI workflows.
• Develop data pipelines and help take models from prototype to production.

ML engineering interns in roles like this rarely spend all day training models from scratch. More often the work is a blend: preparing and cleaning data, experimenting with an approach in a notebook, then doing the less glamorous but crucial engineering to make it reliable in production — wrapping a model behind an API, adding logging and evaluation, and handling the messy real-world inputs users actually send. Expect to iterate quickly, measure whether a change genuinely improves results, and collaborate closely with a small team where your work reaches real users fast.

The modern AI stack, in plain terms

Several terms in this role describe how AI products are built today:

• LLMs (large language models) are the models behind tools like ChatGPT; ML engineers increasingly build features by prompting and orchestrating them rather than training everything themselves.
• NLP (natural-language processing) covers techniques for working with text — extracting information from documents, classifying messages, or answering questions.
• Prompt engineering is the craft of designing the instructions and context given to an LLM so it produces reliable, useful output.
• Agentic AI refers to systems where a model can take multi-step actions — calling tools, retrieving information, and chaining steps — to complete a task rather than just replying once.
• Data pipelines are the plumbing that moves and transforms data so models have clean, timely inputs.

You are not expected to be an expert in all of these; showing that you can learn them quickly is what matters.

Skills that help, and who's a good fit

The strongest candidates for remote ML internships usually have:

• Solid Python, including comfort with libraries such as pandas, NumPy, and at least one ML framework (scikit-learn, PyTorch, or TensorFlow).
• A real project or two — a model you trained, an NLP or LLM app you built, a Kaggle competition, or an open-source contribution.
• Engineering basics — Git, writing clean and testable code, and a working understanding of how to call and deploy an API.
• Self-direction, which is essential in a fully-remote setting where clear written communication and reliable follow-through carry a lot of weight.

To stand out, ship something end to end: deploy a small ML or LLM-powered app, write a short README explaining your approach and results, and be ready to discuss the trade-offs you made.

How hiring usually works, and why this is a strong step

Startups often screen ML interns with a resume review, a short take-home task or coding exercise, and a technical conversation that digs into your projects and ML fundamentals (how a model works, how you would evaluate it, how you would handle bad data). Being able to explain your own project clearly — what you built, why, and what you would improve — usually matters more than memorised theory.

A paid, fully-remote internship at a YC-backed company, working on LLMs and agentic AI with a genuine path to full-time conversion, is an unusually strong early-career opportunity. You gain production AI experience, a recognisable name on your résumé, and the flexibility of remote work — a combination that positions you well for the fast-growing market for ML and AI engineers in India and beyond.

About this listing

Jobsii curates selected opportunities from across the web so you can find them in one place. This role is aggregated from its original source; screening and final decisions are handled by Peakflo on its official application platform. Review the full details on the official page before applying, apply as early as you can because listings can close without notice, and remember that you should never pay money to apply for an internship or job.