Solutions Engineer

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.