Machine Learning Research Engineer

Coders Connect; San Francisco (CA); On-site; USD 200,000 - 350,000; Full time

Benefits offered by this job

Competitive salary

Meaningful early-stage equity

Creative working environment

Job summary

An early-stage AI company in San Francisco is seeking a Machine Learning Research Engineer to own end-to-end research cycles. The role involves training models across creative domains, developing evaluation benchmarks, and collaborating with creative experts and AI labs. The ideal candidate will have 2-6+ years of experience in ML research, strong skills in Python and PyTorch, and a curiosity for subjective AI. This position offers a competitive salary of $200K–$350K and opportunities for equity in the company.

Qualifications

• 2-6+ years in post-training, ML research, or ML engineering.
• Strong experience with Python, PyTorch, LLMs, and multimodal models.
• Proven ability to run fast, iterative experiments from data to evaluation.
• Curiosity for subjective AI—creativity, tone, and aesthetics.
• Low-ego, collaborative mindset; thrives in a small, in-person environment.

Responsibilities

• Train reward models, classifiers, and verifiers across creative domains.
• Develop benchmarks and evaluation methods for subjective tasks.
• Run post-training (RLHF/DPO) experiments on open-source and proprietary models.
• Collaborate with AI labs and creative experts on pilots and research projects.
• Publish findings through blogs and whitepapers.

Skills

Python

PyTorch

LLMs

Multimodal models

Data evaluation

Iterative experimentation

Subjective AI

Job description

We’re partnering with a frontier AI startup

We’re working with an early-stage AI company that’s redefining how models learn to understand subjective quality, from writing tone and design aesthetics to emotional resonance and creative expression.

They’re collaborating with leading AI labs and building new methods that help models reason about creativity, taste, and quality. The founding team is small, highly technical, and deeply curious—building at the intersection of research, product, and creativity.

The Role

As a Machine Learning Research Engineer, you’ll own end-to-end research cycles—designing, running, and analyzing post‑training experiments that help models evaluate style and subjective quality. You’ll collaborate directly with AI labs and creative experts, and have the opportunity to publish your work.

What You’ll Do

• Train reward models, classifiers, and verifiers across creative domains (writing, design, visual style)
• Develop benchmarks and evaluation methods for subjective tasks
• Run post‑training (RLHF/DPO) experiments on open‑source and proprietary models
• Collaborate with AI labs and creative experts on pilots and research projects
• Publish findings through blogs and whitepapers

What We’re Looking For

• 2–6+ years in post‑training, ML research, or ML engineering
• Strong experience with Python, PyTorch, LLMs, and multimodal models
• Proven ability to run fast, iterative experiments from data to evaluation
• Curiosity for subjective AI—creativity, tone, and aesthetics
• Low‑ego, collaborative mindset; thrives in a small, in‑person environment

Bonus

• Experience working with post‑training data or data vendors (Scale, Labelbox, Snorkel, etc.)
• Personal interest in creative fields (design, art, writing, or similar)

Why Join

• Build at the edge of AI and creativity
• Collaborate with frontier research labs
• Work closely with an inspiring founding team in Jackson Square, San Francisco
• Competitive salary and meaningful early‑stage equity

Compensation: $200K–$350K + 0.25–1.5% equity

Interview Process:

We’re proud to partner with a founder who values creativity, collaboration, and curiosity above ego.