Siemens Energy

A Snapshot of Your Day

The day of an ML Developer/MLOps Engineer starts the day by reviewing model performance metrics and identifying any drift in production models. A team meeting follows, where updates on model training and evaluation pipelines are shared. The engineer then works on converting Jupyter notebooks into reproducible training pipelines, ensuring proper version control. After lunch, they package and serve a new machine learning model via Azure ML Endpoints, collaborating with data engineers to manage data and feature pipelines. The day concludes with documenting the integration process and planning for improvements based on stakeholder feedback.

Bridge the gap between data science and production: package models into reliable, secure, and scalable AI applications on Azure, with a focus on automation, observability, and operational excellence. 

How You’ll Make an Impact

• Build, deploy, and operate AI applications as production-grade microservices on Azure (App Services, Container Apps, AKS).
• Develop and maintain robust MLOps CI/CD pipelines for model training, testing, versioning, and deployment.
• Package and serve models as containerized, scalable API endpoints (Docker, Azure Container Services, APIM).
• Implement observability: monitor application performance, model accuracy, and drift; establish alerting, rollback, and retraining strategies.
• Apply software engineering practices to ML workflows: modular design, automated tests, reproducibility, traceability.
• Availability to travel and visit projects.

What You Bring

• Strong proficiency in Python, with experience in ML frameworks such as PyTorch, scikit-learn, and HuggingFace, along with data libraries like pandas and NumPy. Skilled in API development using FastAPI or Flask for serving models into applications.
• Comprehensive understanding of the AI/ML lifecycle, including training, validation, deployment, monitoring, retraining, and scaling of models in production environments.
• Hands-on experience in cloud development, ideally with Azure, including containerization using Docker, and implementation of CI/CD pipelines.
• Practical experience with LLM-based solutions, including RAG pipelines, vector stores, evaluation loops, and basic frontend integration (feedback UIs, annotation loops).
• Familiarity with key MLOps tools, such as MLflow for experiment tracking, feature stores, A/B testing for models, and monitoring frameworks like Prometheus, Grafana, and OpenTelemetry for ML-specific metrics.
• Advanced English proficiency, with strong leadership, communication, and adaptability skills; comfortable working in agile, collaborative environments using Git and version control systems.

About the Team

In the department of Engineering Infrastructure switching configurator, we are responsible for the tool chain for the CPQ process globally. Our team is in Germany and Mexico and our customers are the switching products factory worldwide. You work with software developers, requirement engineers and business analysts.

Who is Siemens Energy?

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/employeevideo 

Our 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

• Career growth and development opportunities
• Supportive work culture
• Company paid Health and wellness benefits
• Paid Time Off and paid holidays
• Savings Fund
• Parental leave and family building benefits

https://jobs.siemens-energy.com/jobs

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