Job
- Level
- Experienced
- Job Field
- Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Hamburg
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop production ML systems for real-time energy trading, enhance MLOps pipelines, and work on the architecture of ML solutions to optimize business decisions.
Job Technologies
Your role in the team
- 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.
- 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.
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Our expectations of you
Education
- Degree in Computer Science, Engineering, Data Science, or similar, as well as fluency in English.
Qualifications
- 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.
- A solid understanding of ML system lifecycle challenges such as deployment, retraining, drift, and reproducibility.
- Vertrautheit mit verteilten oder containerisierten Systemen (Docker, Kubernetes) oder starke Motivation, dieses Skillset zu vertiefen.
- Most importantly: drive, curiosity, and creativity, with a mindset of ownership and a willingness to challenge and improve existing technical choices.
Experience
- Experience working with production ML systems in Python, depth can vary by seniority.
- Interest in or experience with MLOps concepts and automated pipelines.
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What we offer
- 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.
- Vertiefen Sie Ihre Expertise in groß angelegten, Streaming- und Echtzeit-ML-Systemen, die in einem kritischen Geschäftsbereich eingesetzt werden.
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Benefits
Health, Fitness & Fun
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Work-Life-Integration
Topics that you deal with on the job
Job Locations
This is your employer
Vattenfall
Vattenfall is a European energy company with around 20,000 employees. We produce heat and electricity from six different energy sources: Wind, hydro, biomass, nuclear, coal and gas.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Power Sector, Economy
Dev Reviews
by devworkplaces.com
Total
(1 Review)3.6
Engineering
3.0Workingconditions
4.4Career Growth
3.5Culture
3.7
Machine Learning Engineer
- Location
- Hamburg
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
