Founding Optimisation Engineer

Dayjob.AI is looking for a Founding Optimisation Engineer in London, Moorgate. This is a full-time position, on-site or in the office (4 days/week).

Data Science at Dayjob.AI focuses on saving 1% time on the road, which translates to hundreds of thousands more revenue for our customers and saves gallons of diesel on wasted mileage. We’ve launched models to optimise roll-off vehicles in the waste sector; this is just the tip of the iceberg.

What you'll work on:

• Build and own new models that power Dayjob - routing, scheduling and assignment across different verticals of industrial fleets.
• Design, test, and scale optimisation models in real-world environments, then productionise them with the engineering team.
• Work directly with customers to understand the constraints and edge cases that actually decide a plan’s quality.
• Build the tooling to evaluate plan quality, trade-offs, and impact - so we can prove the gain in money, not just in theory.
• Improve runtime, robustness, and solution quality as we scale across more vehicles, customers, and geographies.
• Shape Dayjob’s long-term optimisation and data strategy - and, as we grow, help hire and define the company culture.

What we’re looking for:

• You think in trade-offs, not ideals. Real fleets don’t hand you a clean objective function.
• You’re comfortable balancing competing constraints in a fast-changing system and knowing which ones actually matter to the customer.
• You go where the work is. The best modelling decisions come from understanding how the job really gets done.
• You ship, then sharpen. You prototype quickly, get it live, and improve against real results.
• You’re rigorous and pragmatic. You care about correctness and solution quality while moving at startup speed.
• You’re AI-native in how you work. You already use tools like Claude, Cursor, or similar to extend what you can build.

You may be a good fit if you have:

• A degree in mathematics, physics, computer science, engineering, or a similar quantitative field.
• 4+ years working on optimisation, routing, scheduling, or applied OR problems - ideally with meaningful time on real, deployed systems.
• A track record of building and shipping optimisation or ML solutions, ideally in a fast-paced transport or logistics setting.
• Experience in working with geospatial data like spectral analysis, applied graph theory and computational geometry.
• Strong Python and SQL skills, with hands-on experience using solvers (e.g. OR-Tools, Gurobi, CPLEX).
• The ability to balance theoretical rigour with pragmatic constraints, and to own a model end-to-end: design → build → deploy → tune.
• Comfort working with messy operational data and edge-case-heavy workflows.
• Experience mentoring or leading other engineers, or a clear and genuine ambition to start.

Bonus if you’ve worked on:

• Vehicle routing problems (VRP), especially with uncertainty and problem sizes requiring decomposition.
• Constraint programming or metaheuristics.
• Real-time decision systems.
• Logistics, fleet, or field-service products.
• Early-stage startups.

What we offer:

• Competitive salary.
• Significant equity.
• 25 days holiday + your birthday off.
• Moorgate office.
• Learning opportunities.