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Ricursive Intelligence
AI Chip Design
Last verified August 15, 2026 · Updated daily
What Ricursive Intelligence is building
The chip design industry has a profound bottleneck. Building a single advanced semiconductor, takes teams of hundreds of engineers, 12-18 months of iterative design work, and anywhere from $100M to $650M in engineering labour. The finished chip is already outdated by the time it ships, because AI models have moved on. Ricursive's insight is structurally simple and staggeringly ambitious: use AI to design the chips that train better AI, then use those better chips to design even smarter AI. A recursive loop; hence the name. Their co-founders Anna Goldie and Azalia Mirhoseini proved this was possible at Google with AlphaChip, which compressed chip layout design from multiple months to just a few hours using deep reinforcement learning, and has been baked into multiple generations of Google's TPUs, including v5e, v5p, and the 6th generation Trillium. Ricursive is building a full-stack platform that handles every phase of chip creation - from placement, routing, verification, and architecture search, to using AI agents that get smarter with every chip they design.
Why this matters
The semiconductor industry is a $600B+ market, and it is structurally stuck. The dominant or the 'Big Three', EDA (Electronic Design Automation) tooling vendors, Cadence, Synopsys, Siemens EDA, have barely changed their software paradigm in 30 years. Human engineers are still the bottleneck. AI cannot advance faster than the hardware it runs on, and hardware cannot advance faster than humans can design it. Ricursive attacks that constraint at its root. If their platform delivers even 10x improvement in design throughput, it doesn't just make existing chips cheaper, it makes custom, purpose-built chips (for robotics, drugs, climate, medicine) economically viable for companies that could never afford bespoke silicon before. The downstream effect on the entire AI industry is difficult to overstate. Medicine: Drug discovery today is constrained not just by biology but by compute. Training a protein-folding model or running a molecular dynamics simulation requires months of GPU time on hardware that was designed for general AI workloads, not biochemistry. A purpose-built chip for protein simulation - optimised for the specific mathematical operations that dominate that workload - could cut that timeline by an order of magnitude. The bottleneck preventing its existence has always been cost: a bespoke chip costs $100M+ to design and fabricate. Ricursive's platform, if it works, brings that cost into range for a well-funded biotech, not just a hyperscaler. Climate and energy: Power grid optimisation, weather modelling, and carbon capture simulation are all compute-bound problems that run on chips designed for advertising inference and image generation. The mismatch is enormous. A custom chip for climate simulation would process fluid dynamics calculations - the mathematical core of weather and grid modelling - far more efficiently than anything currently available. The reason it doesn't exist is the same: design cost. Ricursive changes that equation. Robotics: The physical intelligence problem, giving robots the ability to sense, plan, and act in unstructured environments, requires real-time inference at extremely low power budgets. A robot arm running on a GPU draws too much power and generates too much heat. The robotics industry has been waiting for purpose-built inference chips for years; Qualcomm, NVIDIA, and a dozen startups are all trying to solve it. Ricursive's platform, in theory, could compress the design cycle for exactly these chips from 18 months to weeks. The compounding effect is the thing to understand. Faster chip design → better chips → faster AI → better chip design tools → faster chip design again. This is the loop Ricursive is trying to own. It's not a product company in the traditional sense - it's a bid to own the recursive feedback mechanism at the centre of the entire AI economy. That's why Lightspeed and Sequoia invested at a $4B valuation into a company with no product and four months of existence. They're not betting on a tool. They're betting on a new law of the industry.
Open roles at Ricursive Intelligence
5 positions we're tracking. Roles are re-checked daily and removed when filled.
LLM Infra Engineer
First seen 4 months ago
EDA Algorithm Engineer
First seen 4 months ago
LLM Modeling & Scaling Researcher
First seen 4 months ago
Founding Security Engineer
First seen 4 months ago
Operations
First seen 4 months ago
Hiring outlook
$335M raised in 4 months, scaling fast
Working at Ricursive Intelligence
Since , Ricursive Intelligence has built AI Chip Design. The team is now people. For a AI company this size, the reality is opportunity to shape your role based on the company stage.
Most openings are based out of San Francisco.
Frequently asked questions
How many jobs does Ricursive Intelligence have open?
As of February 2025, Ricursive Intelligence has 5 open positions.
Does Ricursive Intelligence hire remotely?
No remote roles right now — all positions are in San Francisco.
What roles is Ricursive Intelligence hiring for?
Ricursive Intelligence is hiring across Engineering, Other, Operations. The most recent opening is LLM Infra Engineer.
How do I apply for a job at Ricursive Intelligence?
Apply via the links above. For tips, read our guide on how to get hired at Ricursive Intelligence.
Where is Ricursive Intelligence based?
Ricursive Intelligence is headquartered in San Francisco.
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