Job description

ABOUT THE ROLE Join an early-stage AI marketing technology company as its first senior AI hire. You will own the quality and intelligence of multi-channel marketing agents, shape the AI architecture and evaluation systems, and help build the AI team as the company grows. WHAT YOU'LL DO - Improve agent output and content quality across social channels and article writing, using evaluation systems to measure results. - Improve search engine optimization and generative engine optimization performance. - Build feedback loops that help agents learn from real-world outcomes and performance signals. - Improve AI infrastructure, agent architecture, model strategy, and supporting data pipelines. - Help hire and lead the AI team as the organization grows. WHAT WE'RE LOOKING FOR - At least 3 years of experience building production machine learning or AI systems, including recent hands-on work shipping LLM products or agents. - Experience designing evaluations and learning from outcome signals at scale in search, ranking, recommendations, or related domains. - Proficiency in TypeScript, including Next.js, and Python for data analysis, evaluations, and model work, with the ability to ship end to end. - Experience building feedback loops and improving production AI infrastructure, agent architecture, or model strategy. - Search, ranking, or AI answer engine experience, particularly involving Google, is valuable. - Experience owning and shipping work in a startup or small team; marketing or go-to-market experience is a plus, as are recommendation systems, algorithms, and reinforcement learning. - Strong technical fundamentals demonstrated through relevant work, research, or comparable accomplishments. COMPENSATION & BENEFITS Target annual compensation is $180,000 to $230,000 USD. Visa sponsorship is available. LOCATION On-site in San Francisco, California.

Requirements

Must-haves

Improve agent output and content quality across social channels and article writing, using evaluation systems to measure results.
Improve search engine optimization and generative engine optimization performance.
Build feedback loops that help agents learn from real-world outcomes and performance signals.
Improve AI infrastructure, agent architecture, model strategy, and supporting data pipelines.
Help hire and lead the AI team as the organization grows.
At least 3 years of experience building production machine learning or AI systems, including recent hands-on work shipping LLM products or agents.
Experience designing evaluations and learning from outcome signals at scale in search, ranking, recommendations, or related domains.
Proficiency in TypeScript, including Next.js, and Python for data analysis, evaluations, and model work, with the ability to ship end to end.
Experience building feedback loops and improving production AI infrastructure, agent architecture, or model strategy.
Search, ranking, or AI answer engine experience, particularly involving Google, is valuable.
Strong technical fundamentals demonstrated through relevant work, research, or comparable accomplishments.
On-site in San Francisco, California.

Nice-to-haves

Experience owning and shipping work in a startup or small team; marketing or go-to-market experience is a plus, as are recommendation systems, algorithms, and reinforcement learning.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningllmtypescriptnext.jspythongo

Platform: ashby
Effort: quick