Machine Learning Research Engineer - LLMs

Applied ML Engineer - LLMs

San Francisco, CA, USA - Onsite

Fulltime Role

Salary: $200K - $300K

Equity: 0.25% - 1.5%

Visa sponsorship available: Simple visa sponsorships and transfers might be possible.

Tech stack: Python, Pytorch, LLMs, Image Models, Multimodal Models, RLHF, DPO

About this role

As a Machine Learning Research 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.

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• 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.