Machine Learning Research Engineer

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

• 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)