Garda Capital Partners
.AI Intern(m/w/x)
VollzeitPraktikumnur vor Ort
Genf, Zug
Neuer Job?Nejo!
Dein persönlicher KI-Karriere-Agent
ENEnerSys
Data Engineering Intern - AI/ML Systems(m/w/x)
Zug
VollzeitPraktikumVor Ort
AI/ML
Nejo KI-Zusammenfassung
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.
Anforderungen
- 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
Aufgaben
- 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
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- SQL
- matplotlib
- seaborn
- Plotly
- Microsoft Azure
- Azure Databricks
- Azure Data Factory
- Azure Data Lake
- Event Hubs
- Spark
- PostgreSQL
- MLflow
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens EnerSys erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Noch nicht perfekt?
- Roche Diagnostics Int. AG
Internship in Innovation & Sustainability(m/w/x)
VollzeitPraktikumnur vor OrtRisch-Rotkreuz - Roche Diagnostics Int. AG
Internship in BGE Development - Production Data Processing(m/w/x)
VollzeitPraktikumnur vor OrtRisch-Rotkreuz - Sonova AG
Data Design Architect(m/w/x)
Vollzeitnur vor OrtSeniorStäfa - Roche Diagnostics Int. AG
Internship fluid handling and workflows(m/w/x)
VollzeitPraktikumnur vor OrtRisch-Rotkreuz
ENEnerSys
Data Engineering Intern - AI/ML Systems(m/w/x)
Zug
VollzeitPraktikumVor Ort
AI/ML
Nejo KI-Zusammenfassung
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.
Anforderungen
- 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
Aufgaben
- 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
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- Python
- SQL
- matplotlib
- seaborn
- Plotly
- Microsoft Azure
- Azure Databricks
- Azure Data Factory
- Azure Data Lake
- Event Hubs
- Spark
- PostgreSQL
- MLflow
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens EnerSys erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Über das Unternehmen
EnerSys
Branche
Manufacturing
Beschreibung
Das Unternehmen ist der weltweit führende Anbieter von Energiespeicherlösungen für industrielle Anwendungen.
Noch nicht perfekt?
- Garda Capital Partners
.AI Intern(m/w/x)
VollzeitPraktikumnur vor OrtGenf, Zug - Roche Diagnostics Int. AG
Internship in Innovation & Sustainability(m/w/x)
VollzeitPraktikumnur vor OrtRisch-Rotkreuz - Roche Diagnostics Int. AG
Internship in BGE Development - Production Data Processing(m/w/x)
VollzeitPraktikumnur vor OrtRisch-Rotkreuz - Sonova AG
Data Design Architect(m/w/x)
Vollzeitnur vor OrtSeniorStäfa - Roche Diagnostics Int. AG
Internship fluid handling and workflows(m/w/x)
VollzeitPraktikumnur vor OrtRisch-Rotkreuz