Hardware Design Validation Engineer - Memory Subsystem
Vals AI
NewWe’re looking for a founding Head of Partnerships to drive the next phase of company growth through Vals Smith, our enterprise product that tells customers which model is best for their use case.
Every large enterprise organization is now being asked to pick model providers, justify the spend, and defend that choice internally. Almost none of them have evidence. They are making seven- and eight-figure decisions on vibes. Early users have already run Vals Smith against their own repositories, and we have more demand than we have capacity to work. In this role you’ll be responsible for generating pipeline, running complex enterprise sales cycles, and building the go to market playbook for Vals Smith from the ground up.
Own the full sales cycle for Vals Smith — outbound, discovery, technical evaluation, negotiation, close, and expansion. Interact with senior leaders and decision makers at large enterprises
Work three pipeline sources from day one: inbound from our launch waitlist and early users, warm introductions from our founders and investors, and cold outbound you generate yourself
Build the playbook, including ICP definition, qualification criteria, outbound sequences, packaging, and objection handling
Work side by side with our founding PM and engineering team. You'll run technical evaluations and POCs together, carry what you hear in deals back into the roadmap and how we package the product
Use data and tooling to continuously monitor impact metrics and optimize strategy
3+ years of enterprise sales experience in SaaS or technology, ideally with exposure to AI. Proven success closing six‑figure deals and managing complex sales cycles with multiple stakeholders.
Relevant and recent experience in outbound prospecting, especially to technical and enterprise personas
You do not need to write code but should have experience selling technical solutions to product and engineering leaders and the ability to translate complex technology into business value.
Comfort operating in an early-stage, high-growth environment, building new motions from scratch and iterating quickly.
Ability to work in-person, in San Francisco. We will support your relocation as needed.
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 housing stipend (within one-mile radius)
Founding team: The core methodology behind this platform 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.
We recently announced our $40M Series A at a $400M valuation, led by Andreessen Horowitz, with participation from existing investors 8VC, Pear VC, and Bloomberg and new investors Hudson River Trading and NextLadder Ventures.
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.
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.
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.
Vals in the Media:
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Vals AI provides independent benchmarking and evaluation for language models and AI applications. It measures performance on realistic, industry-specific tasks in areas such as law, finance, healthcare, tax, coding, and other high-stakes domains. The company publishes comparative reports and leaderboards and works with model labs and enterprises on private evaluations. Vals combines carefully defined tasks, domain experts, grading methods, and reproducible testing so buyers and builders can judge whether a model performs well on the work where it will actually be used.
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