Job Title
Lead AI and Process Modelling Engineer
Salary
Not Disclosed + Equity
Company Description
Alpha Machines is a London-based industrial AI company founded by repeat unicorn builders to reindustrialise Europe through advanced power electronics. They are building AlphaOS, a platform that combines physics-informed modelling with modern ML to design and manufacture critical propulsion systems for aerospace, defence, and robotics applications.
Job Description
As a founding team member, you will own the AI and physics modelling layer of AlphaOS, bridging the gap between thermodynamics and machine learning. You will design prediction, anomaly-detection, and planning surfaces for digital twins, ensuring factory reasoning is grounded in physical truth to optimise yield and throughput for global customers.
Location
London, UK
Why this role is remarkable
- Join a high-caliber founding team led by repeat unicorn founders with a proven track record of scaling massive technology companies.
- Work at the cutting edge of the physical AI revolution, building the software intelligence layer for vertically integrated European manufacturing facilities.
- Enjoy significant impact and ownership as a founding-team member with equity, defining the technical bar for how LLMs reason about physical systems.
What You Will Do
- Architect the AI and physics modelling layer of AlphaOS, encompassing process-level prediction, anomaly detection, and root-cause analysis.
- Encode complex domain physics—including kinetics, thermodynamics, and chemistry—to the digital twin to drive production yield and quality.
- Design and ship LLM-driven reasoning surfaces, such as agents and retrieval systems, that produce actionable outputs for factory operators.
The ideal candidate
- Has 4+ years of experience in applied ML or computational physics, with a background at places like DeepMind, Palantir, or top research groups.
- Possesses expert-level Python skills and fluency in PyTorch or JAX, with a track record of shipping production-grade ML systems.
- Demonstrates deep expertise in physics-informed neural networks, industrial time-series forecasting, or grounding LLM reasoning in structured operational data.
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