AI Engineer
Taste Labs
AI Engineer
Taste Labs
Design taste data for training AI models
About the company
Taste Labs is building the data and infrastructure layer for taste.
Our goal is to end AI slop. To make AI feel right, not just be correct. We raised $18.5M in seed co-led by Amplify and CRV, and most frontier labs are already customers.
AI has nailed objective domains and can generate anything. The hard part left is judgement: what fits, what feels like you, what's actually GREAT. We're turning that into something measurable, starting with design.
We do it on two sides: building the post-training data and RL environments that teach taste to frontier models, and the context and verification tools agents need to produce work that's more creative, more on-brand, more right.
If that problem excites you, you'll like it here!
About the role
You'll build the AI systems that power taste agent harnesses, memory, evals, tooling, data collection, index, search, graph, crawling, scraping, security and more.
Types of problems you’d work on
Craft agent harnesses, memory and self-improvement loops
Design evaluation pipelines and synthetic data generation
Create embedding and retrieval infrastructure that scales to millions of requests
Build crawling and scraping systems for visual data across the web
Set up inference serving and APIs for client-facing products
Manage security sweeps vulnerability mapping
Develop the tooling and infrastructure that makes everything reliable and fast
What matters to us
Deeply technical: you’re deeply opinionated about what good code means, you have an AI-forward setup while being anti-slop, you care deeply about the craft.
You’re creative and have genuine curiosity about ‘taste’ and making subjective domains verifiable
You have startup DNA: you move fast, adapt, no such thing as ‘not in scope’, you like ambiguous, hard problems
AI experience: you need experience building AI forward products, systems, agents, models and more.
You care about arriving at the simple, clear solution vs. the complex one
Bonus points
Open source contributions or personal projects that show you build things because you're curious
Background at creative companies (Figma, Notion, Canva, Adobe, Runway, etc.) or companies with strong index building/crawling (e.g. Firecrawl, Brave, Luma, Pika) or data (Mercor, Surge, etc.)
Design taste data for training AI models
Taste Labs builds the data and infrastructure layer that AI systems use to judge subjective quality, starting with design. The company measures, classifies, and codifies aesthetic judgment into data models that systems can train on, then supplies the context, evaluation, and verification tooling that sits on top. It works with frontier labs on post-training to improve taste and design capability, and with app developers, coding agents, and creative-tool companies checking the design work their models produce. Unlike benchmarks that score correctness, it targets the harder question of whether output is good, on-brand, or right for a particular person. The company's goal is to give models reliable judgment by turning taste into training data instead of leaving it to prompt engineering.
Explore more opportunities at Taste Labs