Lead Modelling Software Engineer

About Homely

At Homely, we’re dedicated to shaping a zero-carbon future. Our smart technology makes it easy for both installers and customers to transition to heat pumps by providing industry-leading heating controls. By predicting and optimising using unique learned house characteristics, time-of-use electricity tariffs, weather forecasts and solar PV data, we lower energy bills and reduce CO2 emissions.

The Role

We’re looking for someone who is ready to take their next step and join us as Lead Modelling Software Engineer to own, scale, and maintain the core predictive and optimisation engines powering our smart controller. This isn't a standard CRUD-app software role: you will be translating the actual physics of home heating and weather forecasting into robust, production-ready code which serves thousands of customers. You'll join a close-knit team where you'll own the full lifecycle of our algorithms, taking ideas from initial research and simulation, building the MVP, and deploying them to our datacentre and on-device ecosystem.

What you'll be doing day-to-day

• Model Production & Optimisation: Translate mathematical formulas, control theory, and thermal dynamics into clean, efficient and maintainable code.
• Taming Real-World Data: Maintain and improve our parameter-finding suite. You’ll figure out how to clean, filter, and make sense of noisy, fragmented telemetry from physical sensors to accurately map out how individual houses heat up and cool down.
• End-to-End Ownership: Take features from a notebook or simulation to an MVP deployment, building code that doesn't break when hit with real-world IoT anomalies.
• Testing & Validation: Build robust testing suites and simulation environments to stress-test optimisation logic against historical tariff, smart meter, and weather datasets.
• Code Quality & Teamwork: Keep our standards high. Participate in code reviews, enforce strict data validation, and collaborate across teams to ensure models integrate smoothly with our production pipelines.
• Keeping Things Running: Keep an eye on how your models perform in the wild, proactively troubleshooting alerts, bugs and quirky edge cases to keep the system stable.

What we're looking for

Background

• Strong Numerical Foundation: A Master’s or PhD in Mathematics, Physics, Engineering, or a highly quantitative field. If you don't have the degree but have proven industry experience doing this exact work, we still want to hear from you.
• Industry Experience: 2+ years of hands-on experience leading a team or managing projects in a technical or engineering role.
• Commercial awareness: Delivering features that are scoped to align with company goals.

Technical Toolkit

• Advanced Python: Comfortable with the classic scientific stack (NumPy, Pandas, SciPy).
• Software Engineering Fundamentals: Solid experience with source control, continuous integration and deployment, writing rigorous unit/integration tests and using Pydantic for strict typing and data validation.
• Dynamical Systems: Familiarity with model predictive control (MPC) and system dynamics.
• Infrastructure: Familiarity with AWS (especially Lambda, DynamoDB, CloudWatch and S3) for deploying and monitoring live models.

Bonus points if you have:

• Low-Level Programming: Experience with C/C++, especially if you’ve optimised code to run close to hardware or within embedded constraints.

What we offer

• We offer a flexible hybrid working arrangement. Office attendance is based on business needs, but you can expect to spend a few days each month with the wider team in our central Manchester office.
• Competitive salary
• Contributory pension
• 25 days holiday plus bank holidays
• Health cover