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Machine Learning Engineer

Vattenfall

Hamburg · On-site Mid Level 1w ago

About the role

About

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.

Responsibilities

In this role, you will actively shape how our ML systems and platform evolve over time, rather than following a fixed blueprint.

  • 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

Growth & Development

This role offers a clear path to grow beyond implementation:

  • Influence ML and data architecture decisions across BA Markets.
  • Develop toward a technical lead or ML architect role over time.
  • Deepen expertise in large‑scale, streaming, and real‑time ML systems used in a critical business domain.

Additional Information

  • Location: Hamburg or Stockholm
  • Application Deadline: 8th of April 2026
  • Application Method: Via our website only. Please upload your resumé as well as a short motivational letter of max. 100 words.
  • Contact for Process Information: Recruiter Jil Ungethüm: +49 40 790221378.
  • Diversity: Vattenfall is committed to diversity and strives to be a good role model. We ensure equal opportunities and rights for all employees regardless of gender, ethnicity, age, transgender identity or expression, religion or other belief, disability or sexual orientation.
  • Trade Union Representatives (Sweden): Akademikerna (Sven-Gunnar Gremlin), Unionen (Anders Bohlin) via Vattenfall's switchboard +46 8 739 50 00.
  • Security Classification: Many positions are security classified. A security clearance will be carried out before employment in accordance with the Security Protection Act. Potential wartime placement is based on the employment contract and the Swedish Total Defence Service Act.

Company Description

Vattenfall is a European energy company with approximately 21.000 employees. For more than 100 years we have electrified industries, supplied energy to people’s homes and modernized our way of living through innovation and cooperation. We are looking for talented individuals who, in addition to their passion for their own role, also have strong team spirit and want to contribute to supporting a meaningful corporate mission.

Right in the heart of Vattenfall, at Business Area (BA) Markets, you will find an inspiring international environment, with a culture of care and personal growth, enabling you to be who you are, having fun, building strong relationships and learning every day. Find out what our colleagues think about our culture: https://youtu.be/-9qGrDUCptA

We employ around 500 professionals who are active across Europe with offices in Sweden, Germany, The Netherlands, and the United Kingdom to drive the energy transition together. Our role in Vattenfall is to maximize the value of the overall portfolio by optimizing and dispatching, hedging, and sourcing for Vattenfall's sales and generation volumes. We serve as Vattenfall’s single access to energy commodity markets and trade electricity, emissions, fuels, freight, and renewable certificates.

In BA Markets the mission of the Unit OU Operations is to drive the digital transformation. OU Operations consists of diverse and highly skilled employees from more than 20 countries. We work internationally from our locations in Stockholm, Hamburg and Amsterdam.

Requirements

  • 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
  • Degree in Computer Science, Engineering, Data Science, or similar, as well as fluency in English

Responsibilities

  • 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

Skills

DockerKubernetesPython

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