Role overview
Within Business Area Markets, business decisions are made around the clock and at high frequency, creating strong opportunities for intelligent automation and applied machine learning.
As an ML Engineer in our Data Science team, you will design, build, and evolve machine‑learning systems that run in production and directly support real‑time electricity trading on the energy markets. Your work has immediate, measurable impact on trading decisions, asset optimization, and business outcomes.
What you'll work on
- Own and develop production ML systems that support real‑time trading and operational decision‑making
- Design and improve MLOps pipelines, including training, deployment, retraining, and monitoring
- Build and operate real‑time inference services, ensuring alignment between batch training and streaming inference
- Contribute to ML and data architecture decisions, including trade‑offs between batch and streaming processing and long‑term maintainability
- Collaborate closely with data scientists, traders, and engineers to translate business needs into robust, scalable ML solutions
*Qualifications
What You Bring**
The position is open to both mid‑level and senior engineers. What matters most to us is drive, creativity, and the motivation to take ownership of impactful technical systems. If you want to influence architecture, challenge existing solutions, and see your work make a real difference, you’ll fit in well.
- Experience working with production ML systems in Python, depth can vary by seniority.
- A solid understanding of ML system lifecycle challenges such as deployment, retraining, drift, and reproducibility.
- Interest in or experience with MLOps concepts and automated pipelines.
- Familiarity with distributed or containerized systems (Docker, Kubernetes), or strong motivation to deepen this skillset.
- Most importantly: drive, curiosity, and creativity, with a mindset of ownership and a willingness to challenge and improve existing technical choices.
- Degree in Computer Science, Engineering, Data Science, or similar, as well as fluency in English