Applied AI Engineer
About
Monogram is the first visual interface for AI.
Our brains are wired for vision. Half of our neural horsepower is dedicated to visual input. Evolution didn't train us to parse bullet points—it trained us to spot tigers in the bushes. That's why we process visuals 60,000 times faster than text and that’s why we are building Monogram, a visual user interface for AI.
Monogram is the first platform that lets LLMs control the entire user experience. By combining voice with UI generated on the fly, we create an experience that’s far more powerful and engaging than a chatbot. We believe this paradigm will redefine how software is built.
This user experience is consistent, as if a single designer crafted entire flows, hundreds of thousands of different interfaces, just for you, just for what you are trying to do at a moment in time, "on the fly", in just 1 or 2 seconds.
We're a deeply technical team of engineers and designers, tucked away in San Mateo, obsessively shaping the next interface for AI. Backed by top-tier investors behind category-defining companies like OpenAI, Anthropic, Meta, Airbnb, Robinhood, Stripe, DoorDash, Shopify, and Slack.
We're building a consumer app powered by this new technology stack. To do this, we're looking for the best Applied AI Engineers in the world. Those who are deeply curious, research-forward, metrics-driven, and excited to build the evaluation layer that helps AI generate better interfaces over time.
What you'll work on
You will build a cutting edge AI evaluation platform to improve our core UI generation model, end to end.
Including:
Tooling for human evaluation.
Automated systems to compare and score UI variations.
Metrics and experimentation system for continuous improvements.
Research evaluation techniques from ML, HCI, UX research and more, there is no blueprint, you’ll invent an AI evaluation system of a new kind.
Prompt engineering, agentic flows and context strategy.
You’d be a great fit if
You’re curious, you have a research-forward mindset, like to read papers, try new approaches
You’re passionate about machine learning and have experience in applied ML
You’re pragmatic and have a gift for translating complex concepts into practical applications
You’ve built experimentation systems and have strong statistical skills.
You can build systems from scratch–solid engineering fundamentals.
You thrive in situations that require ambiguity, exploration, and frontier problem-solving.