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Co-Founder & CTO
San Francisco · On-site · FullTime · Engineering
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About the role
A/B TestingMachine Learning
ABOUT THE ROLE
Join an early-stage creative AI and marketing technology company as an equal co-founder and lead technical and research strategy. You will build a training and evaluation platform for creative AI, grounded in a live product and real-world feedback.
WHAT YOU'LL DO
- Set technical and research strategy, evolving current workflows into a proprietary training and evaluation platform.
- Build data infrastructure connecting briefs, submissions, generation traces, decisions, critiques, and campaign outcomes.
- Develop systems that evaluate, rank, critique, generate, and improve creative work.
- Design allocation policies that direct campaign budgets and inform data collection.
- Make decisions about frontier models, fine-tuning, post-training, reinforcement learning, and original research.
- Build reliable infrastructure for creator workflows, campaigns, experimentation, training, and inference.
- Set standards for data quality, consent, privacy, measurement, and model evaluation.
- Recruit and lead the first engineering and research team, working directly with creators, brands, and investors.
WHAT WE'RE LOOKING FOR
- Hands-on experience with preference or reward models, including RLHF, reward modeling, ranking subjective outputs, or evaluation systems.
- Experience applying causal inference to observational data, including selection bias, off-policy or counterfactual evaluation, adaptive experimentation, or validating proxies against delayed outcomes.
- Experience in production ML, including ads, marketplaces, recommenders, ranking, bandits, or online experimentation tied to business outcomes.
- A track record shipping products used by people and owning model, evaluation, or infrastructure programs end to end.
- Experience learning from noisy, delayed, or subjective outcomes, and recruiting and leading technical teams.
- Research or post-training experience at a leading AI lab or comparable research organization is expected, along with hands-on reinforcement learning or agent training experience.
- Multimodal systems, agents, planning, latent-variable or hierarchical modeling, and prior founder experience are valuable.
- Willingness to commit full-time, in person, with the responsibilities and uncertainty of an early-stage equal co-founder role.
COMPENSATION & BENEFITS
Equity is approximately 28% as an equal co-founder. Cash compensation is discussed based on circumstances and fit. Visa sponsorship is not available.
LOCATION
On-site in San Francisco, California, United States.