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Senior Machine Learning Platform Engineer(m/w/x)
Building and automating data pipelines for ESG risk analysis at a data-as-a-service provider with 200+ employees. Extensive experience with cloud-based distributed systems and ML infrastructure required. 4-week annual work abroad option, paid training days.
Anforderungen
- Strong data or platform engineering skills
- Preference for agile and growing firms
- Background in data and platform engineering
- Experience with cloud-based distributed systems
- Experience with data and ML pipelines
- Experience implementing CI/CD pipelines
- Experience with Data Warehousing technologies
- Experience with LLM and agentic AI
- Experience with Linux system software
- Experience with PostgreSQL or NoSQL
- Strong Python skills
- Knowledge of Git, Docker, and Kubernetes
- Experience in debugging and software testing
- Analytical thinking and organizational skills
- Strong communication skills and English proficiency
- Valid work permit
Aufgaben
- Build and expand the full ML and data pipeline
- Maintain the machine learning and data infrastructure
- Support feature and ETL pipeline development
- Automate data creation processes
- Manage underlying infrastructure and applications
- Design and test production-scale ML models
- Deploy and monitor NLP model endpoints
- Maintain production-scale machine learning models
- Implement CI/CD pipelines for ML applications
- Design and monitor cloud infrastructure
- Optimize systems for efficiency, performance, and cost
- Manage the LLM model lifecycle
- Control access and deployment of LLM models
- Support ad-hoc LLM testing for developers
Berufserfahrung
- ca. 4 - 6 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- AWS
- Linux
- PostgreSQL
- NoSQL
- Python
- Java
- Bash
- Git
- Docker
- Kubernetes
- Kafka
- Amazon Sagemaker
- Databricks
- Airflow
- ML Flow
- Elastic Search
- Kibana
- Grafana
- Terraform
Benefits
Flexibles Arbeiten
- Flexible working hours
- Hybrid work model
- Home office days
Workation & Sabbatical
- 4-week annual work abroad
Weiterbildungsangebote
- Paid training days
Sinnstiftende Arbeit
- Paid volunteering days
Gemeinnützige Ausrichtung
- Charity donation matching
Gesundheits- & Fitnessangebote
- Health and fitness subsidy
Team Events & Ausflüge
- Frequent team events
- Frequent social events
Lockere Unternehmenskultur
- Welcoming office environment
Snacks & Getränke
- Complimentary coffee and refreshments
- Fresh fruit and snacks
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Senior Machine Learning Platform Engineer(m/w/x)
Building and automating data pipelines for ESG risk analysis at a data-as-a-service provider with 200+ employees. Extensive experience with cloud-based distributed systems and ML infrastructure required. 4-week annual work abroad option, paid training days.
Anforderungen
- Strong data or platform engineering skills
- Preference for agile and growing firms
- Background in data and platform engineering
- Experience with cloud-based distributed systems
- Experience with data and ML pipelines
- Experience implementing CI/CD pipelines
- Experience with Data Warehousing technologies
- Experience with LLM and agentic AI
- Experience with Linux system software
- Experience with PostgreSQL or NoSQL
- Strong Python skills
- Knowledge of Git, Docker, and Kubernetes
- Experience in debugging and software testing
- Analytical thinking and organizational skills
- Strong communication skills and English proficiency
- Valid work permit
Aufgaben
- Build and expand the full ML and data pipeline
- Maintain the machine learning and data infrastructure
- Support feature and ETL pipeline development
- Automate data creation processes
- Manage underlying infrastructure and applications
- Design and test production-scale ML models
- Deploy and monitor NLP model endpoints
- Maintain production-scale machine learning models
- Implement CI/CD pipelines for ML applications
- Design and monitor cloud infrastructure
- Optimize systems for efficiency, performance, and cost
- Manage the LLM model lifecycle
- Control access and deployment of LLM models
- Support ad-hoc LLM testing for developers
Berufserfahrung
- ca. 4 - 6 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- AWS
- Linux
- PostgreSQL
- NoSQL
- Python
- Java
- Bash
- Git
- Docker
- Kubernetes
- Kafka
- Amazon Sagemaker
- Databricks
- Airflow
- ML Flow
- Elastic Search
- Kibana
- Grafana
- Terraform
Benefits
Flexibles Arbeiten
- Flexible working hours
- Hybrid work model
- Home office days
Workation & Sabbatical
- 4-week annual work abroad
Weiterbildungsangebote
- Paid training days
Sinnstiftende Arbeit
- Paid volunteering days
Gemeinnützige Ausrichtung
- Charity donation matching
Gesundheits- & Fitnessangebote
- Health and fitness subsidy
Team Events & Ausflüge
- Frequent team events
- Frequent social events
Lockere Unternehmenskultur
- Welcoming office environment
Snacks & Getränke
- Complimentary coffee and refreshments
- Fresh fruit and snacks
Über das Unternehmen
RepRisk AG
Branche
Other
Beschreibung
RepRisk is the world’s most respected Data as a Service (DaaS) company for reputational risks and responsible business conduct.
Noch nicht perfekt?
- RepRisk AG
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