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Founding Research Engineer
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Founding Research Engineer
Founding Research Engineer
Deep Tech Startup | London Compensation: up to £120k base (may increase with next funding round) + founding equity package
About
Building a chip takes hundreds of engineers and years of work. Physical design—the placement, routing, and timing of transistors—is one of the hardest stages: thousands of interdependent decisions, sparse domain data, and no general-purpose AI that understands circuit structures.
This role exists to change that.
You’re joining an early-stage startup backed by top EU investors, building an AI reasoning system for physical chip design. Think of it as analogous to OpenAI’s work in math reasoning: teaching a model to navigate symbolic, graph-structured problems from first principles.
As the first AI hire, you’ll work directly alongside the co-founding team and a founding chip design architect. You’ll have the opportunity to grow into Head of AI as the company scales post-seed.
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What You’ll Do
- Design and build AI reasoning systems that understand circuit structure and make design decisions autonomously
- Develop post-training pipelines—fine-tuning, reward modelling, and feedback-driven learning—on proprietary chip design data
- Create synthetic data generation strategies for a domain with limited open-source examples
- Drive data strategy, model architecture, and inference optimisation across the full AI system
- Collaborate directly with the founding chip design architect to decode problem structures and translate them into training signals
- Shape the technical direction alongside founders:
- Framing problems
- Proposing approaches
- Designing experiments
What You’ll Need
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- Deep, hands-on experience building AI systems for hard, novel domains—reasoning, mathematics, biology, physics, or similar
- Ability to build reasoning models from scratch—post-training, fine-tuning, data strategy—not just deploying existing pipelines
- Strong fundamentals in:
- Model architecture
- Training dynamics
- Inference optimisation
- A first-principles mindset: given a new structured problem, you understand it and build an AI solution from the ground up
- Startup mindset: comfortable balancing ambiguity, realistic deadlines, and rapid prototyping without a large team behind you
Optional Bonus
- Experience with symbolic reasoning, graph-structured data, or formal methods
- Background in post-training for reasoning or mathematics-style models
- Experience generating synthetic data for low-data domains
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