About the role
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 a Founding ML Engineer to own 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 not an MLOps role. You will be researching, training, and shipping models - from paper to prototype to production.
Who you are
- 3+ years building and shipping ML models in production — NLP, information retrieval, or entity resolution
- Strong with transformer architectures — you've trained and fine-tuned encoder models, not just called APIs
- You know how to build and evaluate retrieval systems, classifiers, and embedding models
- Comfortable with contrastive learning, metric learning, and representation learning
- Experience using LLMs for structured extraction, classification, or data generation at scale
- Strong Python and PyTorch
- A true grinder — we work very hard
- Founder mentality — someone who wants to be a founder in the future OR was a founder earlier
What you'll be doing
You'll own the ML systems 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
