Understand real-world energy challenges and turn them into intelligent optimization solutions that make energy systems more efficient, resilient, and sustainable.

You’ll focus on the physics, economics, and control of local energy assets, transforming real-world data into smart automated decisions.

Key responsibilities

• Optimization modeling: Develop and extend deterministic or stochastic optimization models (e.g. MILP) for hybrid systems including PV, BESS, EV charging, CHP, heat pumps and flexible loads.

• Product development: Turn real-world energy problems into product capabilities. Go from idea to prototype to production feature by defining requirements, exploring solution options, and collaborating with engineering to deliver reliable APIs and automated workflows.

• Energy systems analysis: Evaluate system configurations, efficiencies, and operational data to understand real constraints and improvement opportunities.

• Control strategy design: Convert optimization results into robust EMS control logic that operates reliably under dynamic conditions.

• Simulation & evaluation: Develop scenario simulations to test optimization strategies against real-world disturbances (e.g. weather uncertainty, market volatility, grid constraints).

• Continuous improvement: Iteratively refine models and constraints based on on-site feedback, measurements, and performance KPIs (cost, CO₂, grid exchange, etc.).

• Own Delivery End-to-End: You’ll work onsite-first in a cross-functional team with short cycles and fast feedback. From idea to deployment, you drive and own every step of the process.