About the role
AI Intern - Marketing
RippleHire is building the ATS where humans and agents work together. Last year, RippleHire processed 86 million+ candidates across 50+ countries, counting as clients from 2000 employee orgs to 200,000+ employee orgs. We're profitable, and have built a leadership position in IT Services, BFSI, and Professional Services - and we are scouting for an AI intern who will help build AI GTM models and workflows. Internship duration: 3-6 months, full time
What you will do
Depending on the duration of your engagement, you will own one or more of the following workstreams:
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Predictive account intelligence
Build classification models that score accounts and leads against patterns derived from historical conversion data
Incorporate firmographic, behavioural, and technographic signals into feature engineering pipelines
Integrate outputs into CRM as live scoring fields consumed by the sales team daily
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Unstructured data extraction
Design and evaluate LLM-based pipelines that read conversation transcripts and extract structured insights
Benchmark few-shot vs fine-tuned approaches; choose the right method for accuracy and cost
Build evaluation frameworks so output quality is measurable, not subjective
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Buying signal detection
Identify external signals that indicate a target company is in-market for solutions like ours
Build pipelines that aggregate, score, and surface these signals to outbound teams on a regular cadence
Validate signal reliability against actual conversion outcomes over time
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Pipeline analytics
Model deal progression using time-series and survival analysis techniques on CRM event data
Identify leading indicators of deal slippage or acceleration
Produce actionable outputs - not just notebooks, but s and dashboards designed for real time use
What we are looking for
Recent grad or final year student preferably at IIT/NIT
Strong foundations: Proficiency in Python, coursework or projects in ML, NLP, or applied statistics
Builder mindset: You are comfortable working with real world messy, large data sets. You can communicate your findings to non-technical stakeholders in plain language
Nice to have: Prior exposure to B2B, SaaS, or enterprise software contexts — even through internships or projects. Experience with LLM APIs, prompt engineering, or RAG architectures
What you will get
End-to-end ownership of a real project - from problem framing through production deployment
Direct mentorship from the Head of Marketing and close interaction with the product, and engineering teams
A published case study of your work (with appropriate confidentiality) that you can use in placements or grad school applications
Competitive stipend
Fast-track consideration for a full-time role upon graduation for exceptional performers
Share your story
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Which of the four workstreams above would you pick, and why?
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What is one real dataset or project you have worked on that is most relevant — and what did you learn from it that you would not have learned from a textbook?
Attach your resume and any links to code, papers, or public work. We read everything that comes in and respond to every application.