Qualifications
Our Ideal Candidate Has:Exceptional problem-solving and analytical capabilities, enabling them to conceptualize complex systems and convert real-world energy issues into mathematical models. Robust and current expertise in Python, particularly in scientific computing or simulation contexts, with familiarity in libraries such as NumPy, SciPy, Pandas, and Polars. A strong sense of ownership and accountability for key features and systems, grounded in a methodical validation of assumptions and clarity in transitioning from hypothesis to validation. A quality-oriented mindset where testing is integral, along with proficiency in rigorous numerical debugging and identifying edge cases. You will create well-tested, maintainable, and structured systems that operate reliably in production. Comfort with numerical methods and managing extensive time series data, including an understanding of numerical stability, precision, and performance trade-offs. A solid grounding in the mathematics and physics relevant to energy system modeling—such as energy balance, power flows, battery degradation, time-of-use economics, or similar areas that involve applied mathematics and physical constraints. Experience with mathematical optimization is desirable—formulating and solving problems using methods like linear programming (LP) and mixed-integer linear programming (MILP). Familiarity with solvers or modeling frameworks such as PuLP, Gurobi, CPLEX, OR-Tools, and similar is a plus. Experience with automated testing for complex, stateful systems, including strategies for validating simulation outputs and managing floating-point comparisons. Knowledge of data visualization tools and techniques.
About the job
About Gridcog
Gridcog is a SaaS start-up focused on advancing the clean energy transition. The team brings together energy professionals building project modeling software that helps users make informed, strategic decisions about energy projects.
Role Overview
This Senior Simulation Engineer (Modeling) position centers on improving and expanding the simulation and optimization capabilities within Gridcog’s Python codebase. The work blends mathematical modeling, numerical methods, and production-level software engineering to deliver accurate, efficient, and reliable simulations at scale.
What You Will Do
- Enhance and extend simulation and optimization features in the core Python platform
- Work with mathematical models and numerical methods to support complex energy project scenarios
- Ensure modeling outputs remain accurate and efficient as the platform grows
About the Platform
The Gridcog platform models the physical and commercial aspects of energy projects. It integrates technologies such as solar, wind, batteries, flexible loads, gensets, and EV fleets, capturing their interactions within electricity markets and tariff structures worldwide.
Who Should Apply
- Simulation engineers with experience in modeling uncertainty and solving complex business problems
- Candidates with backgrounds in energy systems modeling are encouraged, but those with transferable skills from other modeling or data science domains will also be considered
Location
This position is based in London, England, United Kingdom.
About Gridcog
Gridcog is at the forefront of the clean energy transition, creating innovative software solutions that empower organizations to make effective energy decisions. Our team is comprised of experts who are passionate about utilizing technology to drive sustainable energy practices globally.