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AI/ML Data Engineer with Energy Storage Focus - Leased Labor

Huawei Research Center Germany & Austria

Nürnberg

Vor Ort

EUR 55.000 - 90.000

Vollzeit

Gestern
Sei unter den ersten Bewerbenden

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Zusammenfassung

A global leader in ICT solutions, Huawei, is searching for a skilled AI/ML Data Engineer to join its Nuremberg Research Center. This role focuses on developing innovative data infrastructures supporting AI-driven analytics for energy storage applications, requiring expertise in Python, AI/ML, and Energy Technology. Candidates with a PhD or M.Sc. in related fields are encouraged to apply.

Leistungen

Broad range of training opportunities
Healthy meals in the company canteen
Diverse and welcoming environment
Self-responsible work in a motivated team

Qualifikationen

  • Strong foundation in AI/ML and Energy Storage System technology.
  • Experience integrating ML models into production systems.
  • Good understanding of energy storage systems and related algorithms.

Aufgaben

  • Apply AI/ML techniques to Energy Storage System applications.
  • Design, build, and maintain scalable data pipelines.
  • Collaborate with data scientists to operationalize ML models.

Kenntnisse

Python
AI/ML
Data Engineering
Data Pipeline Design
Predictive Analytics

Ausbildung

PhD in Computer Science, Data Engineering, AI, or related fields
M.Sc. in Computer Science, Data Engineering, AI, or related fields

Tools

Spark
Flink
Kafka
MLflow
Kubeflow
Airflow

Jobbeschreibung

The Power Conversion Technology Laboratory within Huawei’s Nuremberg Research Center is responsible for Advanced Digital Power Technology Research, Architecture Evolution Design and Strategic Technology Planning, and plays an important role in the Huawei Digital Power business in the design and development of power converters and control systems for applications such as PV Solar & Battery Energy Storage Field, Data Centers, Electric Vehicle, and Embedded Power Supply.

We are seeking a highly skilled and motivated Data Engineer with a strong foundation in AI/ML and Energy Storage System (ESS) technology to join our growing energy storage team at Nuremberg research center. This role combines expertise in building scalable data infrastructure with advanced AI model integration to support cutting-edge analytics and intelligent systems for Energy Storage System application. Candidates with a PhD/ M.Sc. in Computer Science, Data Engineering, AI, Energy Technology, or related fields are highly encouraged to apply.

Join us as a

AI/ML Data Engineer with Energy Storage Focus -Leased Labor(m/f/d)

Your mission

  • Apply AI/ML techniques to Energy Storage System applications, including SoH/RUL estimation, fault detection, and predictive analytics.
  • Design, build, and maintain scalable and reliable data pipelines for structured and unstructured ESS data.
  • Collaborate with data scientists and researchers at Huawei to operationalize machine learning models at scale.
  • Work with large-scale data (batch and real-time) using distributed processing frameworks (e.g., Spark, Flink, Kafka).
  • Implement and optimize data architectures for AI use cases, including feature stores and model training pipelines.
  • Ensure data integrity, quality, and security throughout the pipeline lifecycle.
  • Contribute to research-based initiatives such as model experimentation tracking, autoML workflows, or federated learning infrastructure.
  • Provide technical leadership and contribute to the design of AI-infused data platforms.

Your areas of expertise

  • PhD (or Master's with extensive experience) in Computer Science, Data Engineering, AI/ML, Electrical Engineering, Energy Technology, or related disciplines.
  • Good understanding of energy storage systems and familiarity with battery-related algorithms such as SoC, SoH, RUL prediction, and fault detection.
  • Solid programming skills in Python, with experience using PySpark, SQL, and Linux-based environments.
  • Strong understanding of AI/ML concepts and practical experience integrating ML models into production systems.
  • Familiarity with tools like MLflow, Kubeflow, or Airflow for ML pipeline orchestration.
  • Experience working with data lakehouses, streaming architectures, and data governance framework

Preferred Skills

  • Prior work or research in battery management systems or energy storage algorithms.
  • Published research or technical papers in AI/ML, data systems, or energy applications.
  • Experience with vector databases (e.g., FAISS, Pinecone) and LLM-based applications.
  • Familiarity with modern MLOps and DevOps best practices.
  • Contributions to open-source AI or data engineering projects.

By applying to this position, you agree with our Recruitment Privacy Statement. You can read in full our privacy policy here.

Your rewards of working here

  • Our culture is characterized by innovative power and team spirit as well as the intensive exchange of knowledge and experience within our global network.
  • We offer healthy meals ranging from traditional Chinese to western delicacies in our famous company canteen.
  • To keep your development ongoing, you will find a broad range of training opportunities. Many online and face-to-face training programs incl. language courses in German and Mandarin.
  • Our diverse and welcoming environment is shaped by different backgrounds and around 40 individual nationalities.
  • Self-responsible work in a competent, motivated and constantly growing team.

Please send your application and CV (incl. cover letter and reference letters) in English.

Huawei is a leading global information and communications technology (ICT) solutions provider. Driven by a commitment to operations, ongoing innovation, and open collaboration, we have established a competitive ICT portfolio of end-to-end solutions in Telecom and enterprise networks, Devices and Cloud technology and services. Our ICT solutions, products and services are used in more than 170 countries and regions, serving over one-third of the world's population. With 197,000 employees, Huawei is committed to develop the future information society and build a Better Connected World.

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