LumiAIres Ltd
Nonlinear Dynamics & Machine Learning Engineer
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ABOUT LUMIAIRES
LumiAIres is a Scottish deep-tech company developing neuromorphic photonic chips for edge AI applications. Our technology operates at the intersection of photonics, neuromorphic computing, and artificial intelligence, enabling processing speeds and energy efficiencies that conventional silicon-based architectures cannot match.
We are headquartered in Glasgow and are actively deploying our technology across three high-growth sectors: Aerospace, Defence, and Autonomous Systems. Backed by a world-class founding team and currently executing a seed funding round, LumiAIres is at an inflection point and this role is central to our growth trajectory.
THE OPPORTUNITY
This is a research-led role at the mathematical heart of LumiAIres. You will study how our neuromorphic photonic system actually computes, benchmark it rigorously against conventional machine learning, and use what you learn to push its performance further. It is where the theory of nonlinear physical systems meets real machine-learning performance — and it is central to proving, and improving, the advantage our hardware offers. Your immediate focus is our current flagship programme, LUMINA.
Working mainly from measured data and our digital twin rather than at the bench, you will bring the tools of nonlinear dynamics and applied mathematics to bear on a physical learning system: characterising how it behaves and what governs its computational performance, and turning that insight into concrete gains. You will benchmark the system against standard ML baselines on tasks set with the CTO and the Strategic Partnerships Lead, and close the loop through data-driven, hardware-in-the-loop optimisation and control. You will build on the work of the Computational Photonics Engineer, and report to the CTO, who is actively involved in this research.
You will define how LumiAIres measures, understands, and improves the performance of its physical computing platform. As the company scales, this role can grow into ownership of our performance, benchmarking, and optimisation research across the product line.
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KEY RESPONSIBILITIES
The role is structured around four core pillars:
Dynamical-Systems Analysis
- Analyse our neuromorphic photonic system as a nonlinear dynamical system, characterising the properties that govern its computational behaviour.
- Build the mathematical understanding of what drives and what limits its performance, and how operating conditions change it.
- Translate that understanding into concrete guidance for operating points, calibration, and control.
Benchmarking Against Conventional ML
- Benchmark the photonic system head-to-head against standard machine-learning baselines on representative tasks, measuring accuracy, latency, energy, and throughput.
- Run these evaluations rigorously and repeatably, on tasks and datasets set with the CTO and the Strategic Partnerships Lead.
- Produce clear, honest performance evidence for the team, investors, and partners.
Data-Driven Optimisation & Control
- Use data-driven, hardware-in-the-loop methods to drive the system into its best-performing regime and keep it there.
- Develop optimisation and control strategies that improve real-world performance over time.
- Feed results back to the Computational Photonics Engineer and the wider team.
Collaboration & Research Direction
- Work closely with the Computational Photonics Engineer, building on the physics models and digital twin rather than duplicating them.
- Contribute to LumiAIres' core research agenda alongside the CTO and founding team.
- Help shape how the company measures and communicates the advantage of its technology.
WHAT WE ARE LOOKING FOR
A research-minded applied mathematician or scientist who enjoys turning deep theory into practical, measurable results.
- A PhD in applied mathematics, nonlinear dynamics, physics, control engineering, machine learning, or a related quantitative field.
- A strong grounding in dynamical-systems theory: nonlinear dynamics, time-series analysis, and the behaviour of complex physical systems.
- Solid practical machine learning — model training, evaluation, and benchmarking (Python; NumPy / SciPy and PyTorch / JAX or similar).
- Experience with optimisation, and ideally with control or hardware-in-the-loop methods.
- Strong scientific software practice and the ability to turn mathematics into validated, maintainable code.
- Familiarity with physical, analogue, or neuromorphic computing is a strong advantage — formal or informal, and we can support further development.
- Comfort in an early-stage, fast-moving environment where structure is built, not inherited.
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CONTRACT & PROGRESSION
CONTRACT TYPE
18-Month Fixed Term Contract
LOCATION
Glasgow, Scotland (Hybrid)
SALARY
TBC per annum
REPORTS TO
CTO (currently the CEO)
POTENTIAL FOR PERMANENT ROLE
Yes (determined within the first 12 months)
START DATE
To be agreed
This role is offered initially as an 18-month Fixed Term Contract based in Glasgow, with a permanent position anticipated as the company scales.
WHY LUMIAIRES
- Work at the frontier of photonic AI, technology with the potential to reshape how the world processes information.
- A founding team with deep expertise in photonics, neuromorphic computing, and commercial strategy.
- Exposure to global investors, strategic partners, and government stakeholders from day one.
- A genuinely values-led company building for the long term.
- Flexible, trust-based culture with real ownership and impact.
HOW TO APPLY
To express interest in this role, please send a CV and a short covering note describing your background in nonlinear dynamics or applied mathematics, any benchmarking, optimisation, or machine-learning work you have delivered, and what draws you to the mathematics of physical computing.
Applications and initial conversations are treated in strict confidence.
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