
As a Applied AI/ML Engineer, you’ll drive research that teaches models what great feels like across domains such as model personality and behavior, UI design, multi-modal generation, and writing tone. It’s a hard, ambiguous, and (very) cool problem space.
You’ll own full-stack research: experiments, training runs, data and eval pipelines, and publishing results. You’ll develop Taste’s internal research and proprietary models while collaborating directly with AI labs on frontier projects.
What You'll Do
Train reward models, classifiers, and verifiers for subjective domains (e.g. design, writing, visual style).
Develop frontier evaluations and benchmarks for subjective domains.
Run post-training experiments on open-source models to test new data formats and post-training techniques.
Collaborate with AI labs and creative experts to design pilots and experiments around taste.
Own the end to end pipeline.
Publish blogs and whitepapers.
You Might Be a Good Fit If You
Are obsessed with taste and want a world with less AI slop.
Have experience in ML research, Applied ML or ML research engineering, especially in post-training/fine-tuning large models (SFT, RLHF, DPO). Experience with LLM/diffusion models is required.
Think like a researcher, move like an engineer. Are creative, scrappy, and comfortable operating in ambiguity.
Take the next step in your career journey