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AI Summary
Develops decision systems for automated trading of grid-scale batteries and renewable energy assets. Focuses on algorithm design, production software, backtesting, and live performance optimization. Requires expertise in production algorithms, quantitative software, and strong numerical reasoning.
Key Highlights
Develops automated trading algorithms for grid-scale batteries and renewable energy assets
Owns full algorithm lifecycle from design to live performance optimization
Requires expertise in production algorithms, compiled languages (Go/Rust/C++/Java/C#), and quantitative software
Key Responsibilities
Design and develop algorithms for automated trading of energy assets
Build production software for testing, backtesting, and live performance optimization
Ensure algorithms perform reliably in real trading conditions with diagnostics and safe operating responses
Collaborate with product and engineering teams to set measurable outcomes and plan delivery
Review code, improve automated checks, and support safe releases
Explore AI-assisted and agentic tools while maintaining quality controls
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Technical Skills Required
Benefits & Perks
30 days annual leave
Up to 60 days remote work from base country
Professional learning support
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Nice to Have
Experience in battery storage optimization, power trading, or European electricity markets
Scheduling or trading for physical assets
Mathematical optimization, forecasting, simulation, backtesting, or time-series analysis
Python-based data exploration or experimentation
Distributed systems or high-availability software experience
Job Description
Build software that helps flexible energy assets respond to changing power markets.
We’re hiring a senior algorithm specialist for a European company to develop the decision systems behind automated trading of grid-scale batteries and other renewable energy assets. You’ll work across quantitative design, production engineering, and live operations, ensuring algorithms perform well in testing and behave reliably in real trading conditions.
The work
You’ll shape an algorithm from initial problem definition through evaluation, release, and ongoing improvement. That includes:
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