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Location
In office (Stockholm, Berlin)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 8, 2026. First seen by Alion on Sep 11, 2026.

Overview
Company
Impact
Profile match
Tibber is an energy technology company founded in 2016 with its main operations in Stockholm. Its app sells electricity at cost and automates consumption based on hourly prices. The service operates across the Nordics and Germany.

Join Tibber, a company dedicated to revolutionizing the energy market. As a Backend Engineer, you will play a crucial role in transforming our trading models into robust, production-ready systems. You will work closely with our forecasting team and collaborate with traders who rely on your systems' outputs daily. Enjoy flexible work hours, a "no shoe" policy at the office, and the opportunity to work in various locations.

Missions

  • Construire des prévisions qui soutiennent les opérations de trading de Tibber.
  • Faire le lien entre le développement de modèles et les systèmes backend prêts pour la production.
  • Travailler en étroite collaboration avec les traders qui agissent sur les résultats de vos systèmes.

Profil recherché

- Know how to move ML models from development into reliable, production-ready systems

- Are proactive and entrepreneurial, comfortable owning your work end-to-end in a small, high-impact team

- Tibber becomes more AI-enabled and we embrace new tools and ways of working. You don't need to be an expert, but we believe you are motivated by that and excited to grow with it too

- Have a background in energy, utilities, or financial markets, or experience with .NET - a plus, but not required

- Have hands-on experience with time series data and forecasting

- You are driven by impact and know how to turn strategy into execution. You're used to fast-paced environments and thrive when given clear goals and high accountability. We believe you'll thrive here if you:

- Communicate well with both technical peers and business stakeholders

- Have strong Python skills and experience building backend systems in ML-heavy environments (production ML, not just notebooks)

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