Head of Audience

Founding Content Lead

AI moves faster than understanding of it does. New frontier models ship weekly; informed sense of what they actually do well, where they fail, and what to make of them lags by quarters. That gap is where most of the bad takes and the most consequential confusion in the field live. It's also where the most interesting work in AI communication can be done.

Vals is building the work that closes that gap. We run the most rigorous benchmarks in the field, trusted by the frontier labs and the AI research community. We're hiring a Founding Content Lead to take that research and make it part of the broader conversation about AI — not in the diluted, recycled way most AI content lives today, but as the kind of writing that gets read, cited, and remembered.

This is a founding role. You'll own the content function end-to-end: what we publish, how often, where it lives, how it grows. You'll set the editorial voice that becomes the public face of Vals' research and build the audience from the technical community we already reach into the broader world of people who need to understand AI without having time to read every paper. You'll work directly with our CEO on what we say, with our engineering and research teams on the underlying work, and with our designer on how it looks.

Concretely, you'll:

• Build and run the content function — essays, model-release breakdowns, methodology explainers, original analysis — and the cadence, distribution, and growth that make it land.
• Set the editorial voice. Technical enough that ML engineers at frontier labs trust it; sharp enough that smart non-experts can actually use it.
• Ship on news cycle. When a frontier model drops, our analysis is part of the conversation within hours. That's the bar.
• Build the function. Hire the team, set the playbook, raise the bar over time.

Requirements

• A track record building or operating a content brand at scale — paid newsletter, publication, podcast with measurable reach, founding content function at a startup, or a personal Substack you grew to thousands of engaged readers.
• AI fluency. Not necessarily an ML researcher, but you can read a model card, follow a methodology paper, and call out when a benchmark is gamed. You have opinions about which evals are credible and why.
• Speed under news cycles. You've shipped published work within 24 hours of a major industry event and can do it again.
• A distinctive editorial voice — sharp, opinionated, allergic to generic AI commentary.
• Ability to work in-person in San Francisco (preferred — open to discussion for the right candidate).

Nice-to-Haves

• Operator instincts. You pitch and execute without detailed briefs. Likely a former founder, early-stage operator, or content lead at a small team.
• A personal audience of 1,000+ engaged readers on Substack, LinkedIn, X, or equivalent.
• A technical background (CS, EECS, math) you've translated into writing.
• Existing relationships in the AI research community, at frontier labs, or with enterprise AI buyers.
• Visual instincts — can sketch a chart before handing it off to design.

What We Offer

• Highly competitive salary and meaningful equity. Excellence is well rewarded.
• Relocation and transportation support
• Health/dental insurance coverage
• Lunch and dinner provided, free snacks/coffee/drinks
• 401K plan
• Unlimited PTO

About Us

Founding team: The core methodology behind this platform comes from NLP evaluation research we had done at Stanford. We raised a $5M seed from some of the top institutional and angel investors in the valley. Our team has prior work experience at NVIDIA, Meta, Microsoft, Palantir and HRT. Collectively, we have over 300 citations in our published work. Our early team include Stanford PhDs, ex-Jane Street quants, and the first designer at Snorkel.

Tech stack: We use Python for most things at Vals. Our platform is built on Django, with a React frontend. All of the infra is on AWS using CDK for IaC.

What We're Looking For

• Learning velocity: The role encompasses a wide variety of tasks. Rather than expecting you to be an expert on Day 1, we are looking for someone who can learn new skills and technologies extremely quickly.
• Ownership: Working in a small, talent-dense team, we expect everyone to show initiative to build where it's needed, not where it's asked. We strive for autonomy over consensus. This is especially true for this role.
• Intensity: The LLM landscape is constantly changing. Foundation model labs are continuously pushing the frontier. The unicorn companies that will emerge from this technology shift are being built now. Those that win will have an incredibly high speed of execution.
• Solution-oriented mindset: We're looking for people who see opportunities to craft solutions at each juncture, not those who pass hard problems to others or admit defeat.

Further Reading:

• Hugging Face blog on evaluation
• Anthropic's blog on challenges in evaluation
• New York Times article on issues in benchmarking
• Stanford HAI report showing hallucinations in legal tech tools

Referral Bonus

Know someone who would be a good fit? Connect them with View email address on click.appcast.io. If we hire them and they stay on for 90 days you'll get a $10,000 referral bonus and Vals AI merch! Please mention the bonus in your email.