About this role
Overview
As a Solutions Engineer at Quantum Dice, you will help turn probabilistic computing research into practical solutions for real-world industrial problems.
You will work across the full customer journey: understanding operational challenges, translating them into mathematical models, developing Python-based prototypes, benchmarking performance and supporting proof-of-concept delivery.
This is a technical, customer-facing role spanning the Solutions, Applied Research, Engineering and Commercial teams. The work focuses on hard optimisation and decision-making problems across sectors such as defence and national security, logistics and supply chain, telecommunications, energy and financial services. Some defence projects may be classified or export-controlled and will be delivered under the associated handling and security requirements.
You Will Work On
- Translate customer challenges, data and constraints into mathematical and computational models.
- Identify problems suited to probabilistic computing: optimisation, sampling, simulation, inference and decision support, including use cases such as mission planning, routing and scheduling, sensor and resource allocation, network planning, secure logistics and portfolio optimisation.
- Build Python prototypes on Quantum Dice’s simulators, software stack and PPU hardware, plus reusable code and solution templates.
- Apply QUBO, Ising models, Bayesian networks, Boltzmann machines, Monte Carlo and stochastic optimisation.
- Benchmark against classical solvers, CPUs and GPUs, and evaluate solution quality, runtime, scalability and commercial value.
- Deliver technical reports, demonstrations and proof-of-concepts, and support proposals, customer workshops and technical sales discussions.
- Work within relevant defence programme constraints, including security classification, export control, data handling and customer accreditation.
- Feed customer requirements back into Quantum Dice’s product, algorithm and hardware roadmaps.
Who You Are
Required
- Technical degree in Physics, Computer Science, Applied Mathematics, Engineering or Operations Research.
- Strong Python skills and some experience in optimisation, probabilistic modelling, simulation or statistical inference.
- Able to turn open-ended business problems into structured technical models.
- Clear communicator who presents results honestly, without overstating them.
- Enjoys the commercial side as much as the modelling: working directly with customers in a fast-moving deep-tech environment.
Desirable
- MSc or PhD in a relevant discipline.
- Knowledge of QUBO, Ising models, Bayesian inference, MCMC or energy-based models.
- Experience with solvers such as Gurobi, CPLEX, OR-Tools or Pyomo, or stochastic methods such as simulated annealing.
- Customer-facing proof-of-concept delivery, ideally in a deep-tech startup.
- Domain experience in defence, aerospace, government, logistics, telecoms, energy or financial services.
Why Join Quantum Dice?
At Quantum Dice, we're building more than just hardware but creating a new category of computing.
You'll join a team of physicists, engineers, mathematicians and entrepreneurs working to bring probabilistic computing into real-world deployment. You will work directly with leading organisations, influence the future direction of the ORBIT
platform and help define how a fundamentally new computing architecture is applied to optimisation, decision-making and AI challenges in some of the world's most demanding operational environments.