Machine Learning Research Engineer

We’re partnering with a frontier AI startup 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 .

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.

Requirements

• 2–6+ years of professional experience in machine learning research, post-training, or ML engineering

• Strong skills in Python and PyTorch, with hands-on experience training and fine-tuning models

• Deep familiarity with LLMs, multimodal models (text–image/video), and post-training techniques such as RLHF or DPO

• Proven ability to run experiments end-to-end — from dataset design and model training to evaluation and iteration

• Experience developing or using evaluation benchmarks for generative or subjective tasks

• Comfort collaborating in a fast-moving, early-stage environment with limited infrastructure

• Clear, thoughtful communication — you can explain research outcomes to both technical and non-technical collaborators

• A collaborative, low-ego mindset and genuine excitement about building something new

• Interest in subjective or creative domains (e.g. writing, design, visual aesthetics)

• Experience working with or at data vendors (Scale, Labelbox, Snorkel, etc.)

• Prior work with alignment, preference modeling, or reinforcement learning

• A record of publications, blog posts, or open-source contributions in the ML community

Benefits

• Meaningful equity — real ownership in an early-stage, high-impact company

• Competitive compensation ($200K–$350K base)

• In-person, collaborative culture. Work alongside a small, highly talented team in Jackson Square, San Francisco

• Creative research freedom. Autonomy to design, publish, and share your work across open channels

• Partnerships with leading AI labs. Direct exposure to cutting-edge research and experiments

• Growth potential. Shape foundational systems at an early stage and scale with the company

• Support for learning and inspiration. Funding for courses, conferences, or creative exploration related to your work

• Low-ego, non-toxic environment. A team culture built on curiosity, collaboration, and mutual respect