Machine Learning Engineer

Siemens Energy
Mülheim an der Ruhr, Germany
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Artificial Intelligence Continuous Integration Information Engineering Python (Programming Language) Machine Learning Microsoft Office Tensorflow SQL Databases Management of Software Versions Web Services Feature Engineering
+10 more
Data Ingestion Pytorch Large Language Models Model Validation Scikit Learn Information Technology Performance Monitor Feature Selection Machine Learning Operations Api Design

Job description

Remote vs. OfficeHybrid (Remote/Office)CompanySiemens Energy S.r.l.OrganizationSE CFOBusiness UnitGas ServicesFull / Part timeFull-timeExperience LevelProfessional / ExperiencedA Snapshot of Your Day As a Machine Learning Engineer (m/f/d), you are essential for developing, operationalizing, and scaling machine-learning models for finance use cases, aiming to convert data into reliable predictions and support AI-driven decision-making. To achieve this, the role is structured around three core areas: end-to-end AI/ML solution development, specialized data and feature engineering for financial forecasting, and the implementation of robust MLOps for production systems. This focus ensures the creation of scalable, governable, and impactful AI solutions that directly address business problems in the finance domain. Given the focus on advanced model development and productionalization, the ideal candidate will be an expert professional with an advanced degree in a quantitative field. They will possess significant hands-on experience in deploying predictive AI solutions, proficiency in Python and relevant ML frameworks, and a strong understanding of MLOps practices and financial data.How You’ll Make an Impact

  • Design, develop, validate, and deploy end-to-end AI/ML solutions for finance use cases such as forecasting, anomaly detection, and optimization.
  • Lead the full model lifecycle, including data ingestion, model selection, training, evaluation, versioning, and performance monitoring.
  • Run controlled experiments and backtests to quantify incremental value and ensure robustness, particularly for time-series-based models.
  • Ensure all AI/ML solutions meet standards for accuracy, scalability, governance, and responsible AI practices.
  • Engineer high-quality features and predictive signals from internal data, external sources, and LLM-derived inputs.
  • Apply dimensionality reduction and advanced feature selection to build compact, interpretable, and high-performing predictors.
  • Implement MLOps practices such as automated monitoring, drift detection, retraining triggers, and rollback strategies for production models.
  • Deploy production-grade APIs and services and collaborate with stakeholders to translate business problems into measurable AI/ML outcomes while mentoring team members.

Requirements

  • Advanced degree (Master’s or PhD) in a quantitative field such as Computer Science, AI, Statistics, Applied Mathematics, or Econometrics.
  • Hands-on professional experience developing and deploying production-grade AI/ML and predictive solutions.
  • Experience applying AI/ML techniques in the finance domain is a strong advantage.
  • Strong expertise in AI/ML development using Python with frameworks such as PyTorch, TensorFlow, and Scikit-Learn.
  • Proven skills in feature engineering, signal engineering, and forecasting for predictive modeling.
  • Solid background in MLOps and data engineering, including SQL, CI/CD pipelines, and API development.
  • Experience operationalizing models through robust MLOps practices and scalable production workflows.
  • Demonstrated thought leadership and the ability to work effectively within Agile development environments.

About the company

Siemens Energy and Siemens Gamesa are becoming Omterra. ‘We energize society’ by supporting our customers to make the transition to a more sustainable world, based on innovative technologies and our ability to turn ideas into reality. With nearly 100,000 employees around the world, we shape the energy systems of today and tomorrow., At Siemens Energy, we are more than just an energy technology company. With ~100.000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world’s electricity generation.

Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation. Find out how you can make a difference at Siemens Energy: https://www.siemens-energy.com/employeevideoOur Commitment to Diversity Lucky for us, we are not all the same. Through diversity we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character - no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences. Rewards/Benefits

  • In addition to an attractive remuneration package in line with the market, you can expect an attractive employer-financed company pension scheme
  • We also offer the opportunity to become a Siemens Energy shareholder
  • We offer our employees the opportunity to work flexibly and remotely, and our inspiring offices provide space for collaboration and creativity
  • The professional and personal development of our employees is very important to us. We provide them with the opportunities to learn and develop in a self-determined way, various attractive programmes and learning materials are available for this purpose
  • In relation to the ‘compatibility of family and work’, we have a wide range of offers, e.g. flexible working time models, childcare places at many locations, the possibility of trial part-time work or even a sabbatical

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