Full-Time
Member of Technical Staff
Platform
Updated on 9/16/2026
Vals AI
11-50 employees
Independent AI model evaluation platform
Compensation Overview
$140k - $185k/yr
San Francisco, CA, USA
In Person
In-person team based in San Francisco; relocation or transportation support is available.
 Software Engineering (1) |
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- You can build and ship quickly with high quality and have a track record of building things of significant scope within jobs, side projects, or open source.
- You have significant professional experience with Python.
- You are familiar with system-design concepts including virtual machines, containerization, load balancers, and databases, and understand when to use them appropriately.
- You have experience working with large language model APIs and understand concepts such as temperature, tokenization, and reasoning.
- You have experience working with development sprints, Git workflows, and pull request reviews.
- You can provide and receive feedback effectively through spoken and written communication, including design documents.
- You are comfortable breaking ambiguous problems into clear and actionable steps.
- You can develop and iterate quickly.
- You are available to work in person in San Francisco.
- Build distributed systems to run evaluations across multiple models, benchmarks, and machines at scale.
- Deploy cloud infrastructure using infrastructure as code, including deployment pipelines, servers, logging, and monitoring.
- Contribute to the internal and external libraries maintained by the company, including the public model library.
- Develop full-stack platform features using React and TypeScript on the frontend and Python and Django on the backend.
- Perform code and architecture reviews for other team members.
- Help establish engineering best practices across the organization.
- Collaborate closely with the research team to ensure the infrastructure meets its needs.
- Experience with frontend development, ideally React.
- Experience with Django, FastAPI, or other Python-based HTTP servers.
- Experience working with Amazon Web Services infrastructure, including infrastructure as code.
- Experience at early-stage startups or running your own company.
- Interest in artificial intelligence and machine-learning systems and evaluation.
Vals AI provides independent evaluation and benchmarking for large language models and AI applications. It builds domain-specific leaderboards and benchmarks (finance, law, healthcare, software) using private datasets to prevent test leakage, and it measures performance on real-world tasks and capabilities like tool use, multi-modality, reasoning, accuracy, latency, and cost. The platform offers an evaluation infrastructure for private labs and enterprises to test their own data and tasks, and it also maintains public benchmarks such as Finance Agent and the Valkyrie evaluation framework. Its goal is to give neutral, practitioner-focused metrics that help research labs and enterprise teams choose and deploy AI models with confidence.
Company Size
11-50
Company Stage
Series A
Total Funding
$40M
Headquarters
San Francisco, California
Founded
2023
Get referred to Vals AI
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Simplify's Take
What believers are saying
- On August 13, 2026, Vals raised $40 million from a16z at $400 million.
- Vals said revenue grew eightfold, customers doubled, and headcount tripled in six months.
- CoreWeave collaboration on RSI Index expands Vals into frontier-risk and governance debates.
What critics are saying
- OpenAI, Anthropic, Google, and xAI can optimize against Vals outputs within months.
- Private datasets do not stop benchmark saturation; Vals must constantly invent harder tasks.
- If customers doubt neutrality after one benchmark dispute, Vals' trust-layer thesis collapses.
What makes Vals AI unique
- Vals AI sells private, domain-specific benchmarks, not generic academic leaderboards.
- On August 13, 2026, Vals launched Vals Smith, RSI Index, and Vals Index 2.0.
- Vals rotates benchmarks like CorpFin to preserve differentiation as frontier models improve.
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Benefits
Health Insurance
Dental Insurance
401(k) Retirement Plan
Unlimited Paid Time Off
Meal Benefits
Company Equity
Relocation Assistance
Growth & Insights and Company News
6 month growth
↓ -4%1 year growth
↓ -14%2 year growth
↓ -25%Vals AI built a test to see if AI models can create their own successors, and the results are fascinating. The Recursive Self-Improvement Index offers the first standardized way to measure whether AI systems can autonomously advance their own development. 2 hours ago Sponsored: CryptoSlots - Cryptoslots Play now! If you've ever wondered how close Crypto Briefing is to AI systems that can design better versions of themselves, Vals AI just built the scoreboard. The company's Recursive Self-Improvement Index, or RSI Index, attempts to quantify something that until now has lived mostly in the realm of theoretical worry: how capable are today's frontier models at conducting the research and development needed to build their successors? The top-performing model on the index, Claude Fable 5.1, scores 35.03%. Which sounds low until you understand the scale. How the RSI Index actually works. Vals AI designed the index around five specific tasks that mirror the real workflow of AI development. Models are evaluated under fixed compute and time constraints, meaning they can't just brute-force their way to a good score by burning through unlimited resources. The scoring system is anchored to reference points rather than arbitrary grades. A score of 0 represents a baseline, 0.5 maps to performance levels already documented in published research, and a theoretical optimum sits at 1. Claude Fable 5.1's score of 35.03% means it's performing meaningfully but still falls short of replicating techniques already known to researchers. The models can outperform existing techniques in experiment execution but generally lag in producing novel techniques. Why this matters now. The RSI Index launched in August 2026 through a collaboration between Vals AI and CoreWeave, timed alongside the company's $40 million Series A funding round. That round valued Vals AI at $400 million. CEO Rayan Krishnan has positioned the index as filling a critical gap. Major AI labs have already started referencing recursive self-improvement potential in their model cards, but without a standardized framework for comparison, those references lack a common basis for evaluation. In the six months following its funding round, Vals AI's revenue grew 8x compared to all of 2025. Its customer base doubled. Its staff tripled. The governance question. Krishnan has been vocal about what the RSI Index implies for regulation. The concern isn't that a model scoring 35% is about to go rogue. It's that the trajectory from 35% to higher scores could be steep, and the development of these capabilities is happening inside a handful of labs with limited external visibility. Krishnan has emphasized the need for international governance structures to keep pace with these advancements. The RSI Index gives it empirical grounding: it's harder to dismiss calls for oversight when you can point to a concrete metric showing measurable progress toward autonomous self-improvement. Disclosure: This article was edited by Editorial Team. For more information on how Crypto Briefing create and review content, see its Editorial Policy.
Vals AI. Vals AI raises $40M Series A. Vals AI, a San Francisco-based AI agent testing platform, raised $40 million in a Series A fundraising round led by Andreessen Horowitz a16z with participation from 8VC and Pear VC.
Vals AI raises $40M Series A. Vals AI raises $40M Series A led by a16z at a $400M valuation to expand its independent AI evaluation and benchmarking platform. Updated August 13, 2026 Vals AI raises $40M Series A at $400M valuation. Vals AI, an artificial intelligence evaluation startup, has announced a $40 million Series A funding round at a $400 million valuation. The company focuses on providing independent benchmarks for artificial intelligence models, helping enterprises, labs, and governments measure model performance and ROI across various professional domains. Investors. The round was led by a16z, with participation from existing investors 8VC and BloombergBeta, as well as new investors HRT Ventures and Next Ladder Ventures. Vals AI use of funds. Vals AI plans to use the capital to support its continued growth as an independent evaluator of artificial intelligence, including expanding its team and enhancing its benchmark infrastructure and testing capabilities. About Vals AI. Vals AI is an independent AI evaluation company that develops benchmarks and evaluation tools to measure the capabilities and performance of artificial intelligence models. The company evaluates AI systems on real-world tasks across industries including law, banking, engineering, and healthcare, helping enterprises, AI labs, and governments assess model performance, risks, and progress. Funding details. Company: Vals AI Raised: $40M Round: Series A Funding Date: August 13, 2026 Lead Investor: a16z Additional Investors: 8VC, BloombergBeta, HRT Ventures, Next Ladder Ventures Company Website: https://www.vals.ai/ Software Category: Artificial Intelligence Source: https://www.vals.ai/blogs/series-a Updated August 13, 2026
Vals AI raised $40 million in Series A funding led by a16z to build independent benchmarks evaluating AI models on real-world tasks in finance