Job Specifications
About The Role
Skills: Python, PyTorch, NLP, LLMs, Information Retrieval, Entity Resolution, Text Classification
We're building the gateway to the internet for AI agents. Our APIs already power hundreds of customers — and we went from 0 to $7M ARR in our first 12 months. Now we need someone who can push the boundaries of what our ML systems can do.
We're hiring an ML Engineer Intern to work directly with our founding team on the research and engineering behind our core intelligence layer. Our platform indexes hundreds of millions of professional profiles and company records from across the web. Making that data searchable, matchable, and enriched is an ML problem at its core.
This is a 12-week summer internship (June–August 2026). You will not be fetching coffee or watching from the sidelines. You will be researching, training, and shipping models — from paper to prototype to production. Previous interns' work has shipped to customers within weeks.
Who you are
Currently pursuing a Master's or PhD in Computer Science, Machine Learning, NLP, or a related field
Strong fundamentals in NLP, information retrieval, or entity resolution — through coursework, research, or side projects
Familiar with transformer architectures — you've trained or fine-tuned encoder models, not just called APIs
Experience building retrieval systems, classifiers, or embedding models (in academic or personal projects)
Exposure to contrastive learning, metric learning, or representation learning
Have used LLMs for structured extraction, classification, or data generation
Strong Python and PyTorch
A true grinder — we work very hard
Founder mentality — someone who wants to build a company someday
What you'll be doing
You'll own real ML problems that turn messy, multilingual, web-scale data into structured intelligence. Some example problems:
A customer searches for "RevOps professionals" — you need to return people titled "Head of Revenue Department," "Revenue Operations Manager," and "VP Sales Operations," across English, French, and German
Three different data sources list what looks like three different companies — but it's actually one. You figure out how to resolve that automatically across millions of records
Given raw people data, infer the org chart — who reports to whom, what the team structure looks like, how the engineering org differs from sales
Detect what technologies a company uses from unstructured signals scattered across the web
Classify whether a job change was a promotion, lateral move, demotion, or just a title edit — and do it for millions of transitions
Map raw job titles to canonical titles, seniority levels, and job functions — across dozens of languages and naming conventions
Nice to haves
Published research or conference papers (NeurIPS, ICML, ICLR, ACL, EMNLP, etc.)
Experience with entity resolution or record linkage at scale
Built taxonomy or ontology systems over messy real-world data
Background in multilingual NLP or cross-lingual transfer
Open-source contributions in NLP/IR
Experience with distributed training on GPU clusters
Compensation & perks
$8,000–$14,000/month (above market rate for SF internships)
Housing stipend for those relocating to SF
Direct mentorship from the founding team — no layers between you and the CEO
Your work ships to production and reaches real customers
About the Company
People and Company Search for AI Power any AI agent in sales, recruitment and investment with the freshest, most trusted data. The only platform providing truly real-time data to power your intelligence layer. Customers use us to build their AI agent platforms and applications over our trusted data. We power builders of: -AI SDRs -AI sales platforms -AI recruiting platforms -AI investment/due diligence platforms -Internal sales or marketing platforms We serve use cases like: automatic pipeline building, pipeline prioritizati...
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