Lead enterprise marketing strategy and execution at Vals AI to establish credibility in AI model performance.
Posted by employer 2 days ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
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Not disclosed in this posting: compensation, years of experience, visa sponsorship.
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Joblaze summary
The Enterprise Marketing Lead at Vals AI is responsible for shaping and executing the marketing strategy aimed at enterprise clients, focusing on effective messaging and targeted content distribution. This role requires a strong background in B2B marketing for technical products, along with the ability to produce compelling content that resonates with enterprise audiences. Ideal candidates will have experience in research communications or technical writing, and should be comfortable working in a fast-paced environment alongside a highly skilled team. Vals AI is in a growth phase, having recently secured significant funding, and emphasizes a culture of ownership and rapid execution.
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From the original posting
We’re hiring an Enterprise Marketing Lead to oversee strategy and execution for Vals AI’s marketing efforts to enterprises: positioning and what stories we tell, which audiences we tell those stories to, which channels we use to tell those stories. Your goal is to establish Vals AI as a credible source of information on model performance within the enterprise community to foster adoption of our enterprise product.
You’ll work closely with the Vals Smith team, our researchers, our marketing and design teams, and our co-founders to be successful. We want someone who can understand the underlying work and develop a distinctive point of view on what matters. The goal is to make Vals one of the most trusted voices on how AI is actually performing — in benchmarks, inside companies, and as the technology becomes important enough to require better standards around how we measure it.
Own Vals’s enterprise positioning and messaging, working directly with our CEO, researchers, and engineers.
Prioritize which customers to target and which personas within them matter most.
Produce content that makes Vals the go-to way for enterprises to evaluate models and agents on their own workflows: product launches, customer stories, technical case studies, and original analysis.
Pick the right distribution channel for each piece of content and each persona.
Experience owning positioning and go-to-market for a technical B2B product
A track record of building distribution for content, not just producing it
A portfolio of writing (e.g., published essays, research blog posts, lab posts, or industry reporting.) Ideally, with experience creating content for enterprise and/or technical audiences
Technical fluency. You don't need to be able to train a model, but you need to be able to read a paper, sit in on a research review, and come out with something accurate and sharp.
An editorial point of view. You should have opinions about what's interesting, drive decisions, push back on weak takes, and not just transcribe what people say.
Speed and self-start mindset. We ship content the day a major model releases. You should be able to turn around a publishable post in hours, not weeks, with limited oversight.
Ability to work in person 5 days a week in San Francisco.
Prior research communications experience at an AI lab or research-led startup
Prior writing for a technical publication or engineering blog
Highly competitive salary and meaningful ownership. Excellence is well rewarded.
Relocation and transportation support
Full health, dental, and vision insurance coverage
Lunch and dinner provided, free snacks/coffee/drinks
401K plan
Unlimited PTO
$1,500 monthly housing stipend for living within one mile of the office
Founding team: The core methodology behind Vals AI comes from NLP evaluation research we had done at Stanford. We work with all the major foundation model labs, some of the largest financial institutions, and hospital systems in the world. 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 includes Stanford PhDs, ex-Jane Street quants, and the first designer at Snorkel.
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 quickly.
Vals in the Media:
Standard company text repeated across Vals AI's postings is omitted here.
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