Garda Capital Partners
.AI Intern(m/w/x)
Full-timeInternshipOn-site
Genf, Zug
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ENEnerSys
Data Engineering Intern - AI/ML Systems(m/w/x)
Zug
Full-timeInternshipOn-site
AI/ML
Nejo AI Summary
Designing data infrastructure and building ingestion pipelines for AI/ML systems in energy management and asset monitoring. Master's or PhD in a technical field, Python, and SQL proficiency required. Focus on feature engineering and data quality for complex datasets.
Requirements
- Master's or PhD in Computer Science, Data Science, Electrical Engineering, or related field, or recent graduation
- Strong proficiency in Python for data manipulation, transformation, and pipeline development
- Solid experience with SQL and relational or time-series data systems
- Understanding of machine learning workflows, training data, feature engineering, inference pipelines, and data quality impact
- Hands-on experience with large, complex datasets, including missing data, schema inconsistencies, temporal alignment, and high-cardinality variables
- Strong data visualization skills with matplotlib, seaborn, or Plotly; clear, informative, reproducible analysis outputs
- Familiarity with cloud data platforms, particularly Microsoft Azure (e.g., Azure Databricks, Azure Data Factory, Azure Data Lake, or Event Hubs); equivalent experience with other major cloud providers
- Exposure to large-scale or streaming data concepts, including real-time ingestion, event-driven architectures, or distributed data processing frameworks (e.g., Spark)
- Experience with relational or analytical databases (e.g., PostgreSQL); awareness of modern storage formats or database categories (columnar, vector, graph) is a plus
- Hands-on ML experience, including model training, feature engineering, or experiment tracking (e.g., MLflow); understanding of data pipeline impact on model performance
- Interest in or prior exposure to time-series sensor data, industrial telemetry, battery systems, or energy infrastructure is a plus
Tasks
- Design data infrastructure for AI/ML projects
- Build data ingestion pipelines for various data types
- Implement data transformation and validation processes
- Develop data quality and monitoring frameworks
- Construct feature engineering pipelines with AI/ML engineers
- Optimize data models for time-series and ML consumption
- Evaluate storage formats and database architectures
- Contribute to streaming data pipeline development
- Support real-time ingestion and event-driven architectures
- Generate synthetic and simulation data for digital twin platforms
- Develop exploratory data analysis and visualizations
- Test and validate data pipelines
- Verify data contracts and perform simulation testing
- Create technical documentation and reports
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- SQL
- matplotlib
- seaborn
- Plotly
- Microsoft Azure
- Azure Databricks
- Azure Data Factory
- Azure Data Lake
- Event Hubs
- Spark
- PostgreSQL
- MLflow
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of EnerSys and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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ENEnerSys
Data Engineering Intern - AI/ML Systems(m/w/x)
Zug
Full-timeInternshipOn-site
AI/ML
Nejo AI Summary
Designing data infrastructure and building ingestion pipelines for AI/ML systems in energy management and asset monitoring. Master's or PhD in a technical field, Python, and SQL proficiency required. Focus on feature engineering and data quality for complex datasets.
Requirements
- Master's or PhD in Computer Science, Data Science, Electrical Engineering, or related field, or recent graduation
- Strong proficiency in Python for data manipulation, transformation, and pipeline development
- Solid experience with SQL and relational or time-series data systems
- Understanding of machine learning workflows, training data, feature engineering, inference pipelines, and data quality impact
- Hands-on experience with large, complex datasets, including missing data, schema inconsistencies, temporal alignment, and high-cardinality variables
- Strong data visualization skills with matplotlib, seaborn, or Plotly; clear, informative, reproducible analysis outputs
- Familiarity with cloud data platforms, particularly Microsoft Azure (e.g., Azure Databricks, Azure Data Factory, Azure Data Lake, or Event Hubs); equivalent experience with other major cloud providers
- Exposure to large-scale or streaming data concepts, including real-time ingestion, event-driven architectures, or distributed data processing frameworks (e.g., Spark)
- Experience with relational or analytical databases (e.g., PostgreSQL); awareness of modern storage formats or database categories (columnar, vector, graph) is a plus
- Hands-on ML experience, including model training, feature engineering, or experiment tracking (e.g., MLflow); understanding of data pipeline impact on model performance
- Interest in or prior exposure to time-series sensor data, industrial telemetry, battery systems, or energy infrastructure is a plus
Tasks
- Design data infrastructure for AI/ML projects
- Build data ingestion pipelines for various data types
- Implement data transformation and validation processes
- Develop data quality and monitoring frameworks
- Construct feature engineering pipelines with AI/ML engineers
- Optimize data models for time-series and ML consumption
- Evaluate storage formats and database architectures
- Contribute to streaming data pipeline development
- Support real-time ingestion and event-driven architectures
- Generate synthetic and simulation data for digital twin platforms
- Develop exploratory data analysis and visualizations
- Test and validate data pipelines
- Verify data contracts and perform simulation testing
- Create technical documentation and reports
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- SQL
- matplotlib
- seaborn
- Plotly
- Microsoft Azure
- Azure Databricks
- Azure Data Factory
- Azure Data Lake
- Event Hubs
- Spark
- PostgreSQL
- MLflow
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of EnerSys and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
EnerSys
Industry
Manufacturing
Description
Das Unternehmen ist der weltweit führende Anbieter von Energiespeicherlösungen für industrielle Anwendungen.
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