Applied ML Engineer

Tastelabs; San Francisco (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

Tastelabs in San Francisco is looking for a talented Machine Learning Engineer to spearhead full-stack ML experiments. You'll train models and publish insightful results while collaborating on cutting-edge projects.

The ideal candidate is passionate about taste and design, has experience in post-training ML, and thrives in a fast-paced startup environment. Join us in building a world with less AI slop!

Qualifications

• Obsessed with taste and desire a world with less AI slop.
• Experience in post-training and evaluations in subjective domains.
• Ability to think like a researcher and move like an engineer.

Responsibilities

• Train reward models, classifiers, judges, and verifiers.
• Develop frontier evaluations and benchmarks.
• Run post-training experiments on open-source models.
• Set up infrastructure for evaluations.
• Collaborate on design pilots and experiments around taste.
• Own the end-to-end pipeline.
• Publish blogs and whitepapers.

Skills

Experience in post-training and evals/judges

LLM experience

Creative problem-solving

Collaboration with AI labs

Publishing blogs and whitepapers

Job description

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 own full‑stack ML experiments, training runs, infra, data and eval pipelines, and publishing results. You’ll develop Taste’s internal research, evaluation design, judges and reward models while collaborating directly with AI labs on frontier projects.

What You'll Do

• Train reward models, classifiers, judges, 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.
• Set up the infrastructure to run this.
• 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 post‑training and in evals/judges.
• Have LLM experience; cannot be purely classical ML.
• Think like a researcher, move like an engineer. Creative, scrappy, comfortable in ambiguity.
• Have startup experience strongly preferred; deep passion for creativity and design.