# **Founding Optimisation Engineer**
London, Moorgate · Full-time · On-site or in Office (4 days/week) · Data Science & Operations Research · [Dayjob.AI](http://Dayjob.AI) · YC P26
**About DayJob**
DayJob builds AI agents for short-haul trucking - a **$45bn market** still run on spreadsheets, phone calls and software from the 1990s.
We've just completed **Y Combinator** , are scaling towards **$1M ARR** , growing ~20% month-on-month, and launching in the US. Our customers include some of the largest waste and recycling operators in the UK and US, and we're backed by leading investors including **Paul Graham** (Founder of Y Combinator) and **Harry Stebbings** (Founder of 20VC).
Dayjob has developed its own proprietary models, which wouldn’t have been possible until now, delivering hundreds of thousands of pounds in additional revenue to its customers. This is a once in a generation opportunity to change how these businesses operate, industries where software adoption has been slow but where AI adoption can completely change their economics.
**About the Optimisation Team**
Deploying state-of-the-art algorithms into legacy businesses is one way to think about what we do at Dayjob. Hence, optimisation is the cornerstone of what we do; saving 1% time on the road gives our customers hundreds of thousands more revenue 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.
**Founding Team**
Fred & George met at the University of Oxford.
- George (CEO) was Head of Sales at Otta and launched Deliveroo’s Grocery division, scaling it to £100M GMV.
- Fred (CTO) builds products that optimise complex supply chains using AI and advanced analytics.
**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, 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 & development budget
- A foundational role defining our optimisation engine and technical roadmap from the ground up
**Application process**
1. Intro call with the team (30 mins)
2. Technical interview (2 hrs)
3. Final chat with the founders (45 mins)
**To close**
Short-haul trucking is a decade behind companies like Amazon - yet it's the lifeblood of the economy. Our customers deserve better tools, and only now, with AI, are they possible to build. If you want to build the brains of the next-generation dispatch engine, we'd love to meet you.
Visa sponsorship is not available for this role.
