Zühlke Engineering AG
Lead Data Architect(m/w/x)
Full-timeWith HomeofficeSenior
Schlieren
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RERepRisk AG
Senior Machine Learning Platform Engineer(m/w/x)
Zürich
Full-timeWith Home OfficeSenior
AI/ML
Data Science
Nejo AI Summary
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.
Requirements
- 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
Tasks
- 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
Work Experience
approx. 4 - 6 years
Education
Bachelor's degreeORMaster's degree
Languages
English – Business Fluent
Tools & Technologies
AWSLinuxPostgreSQLNoSQLPythonJavaBashGitDockerKubernetesKafkaAmazon SagemakerDatabricksAirflowML FlowElastic SearchKibanaGrafanaTerraform
Benefits
Flexible Working
- •Flexible working hours
- •Hybrid work model
- •Home office days
Workation & Sabbatical
- •4-week annual work abroad
Learning & Development
- •Paid training days
Purpose-Driven Work
- •Paid volunteering days
Social Impact
- •Charity donation matching
Healthcare & Fitness
- •Health and fitness subsidy
Team Events
- •Frequent team events
- •Frequent social events
Informal Culture
- •Welcoming office environment
Snacks & Drinks
- •Complimentary coffee and refreshments
- •Fresh fruit and snacks
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of RepRisk AG 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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RERepRisk AG
Senior Machine Learning Platform Engineer(m/w/x)
Zürich
Full-timeWith Home OfficeSenior
AI/ML
Data Science
Nejo AI Summary
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.
Requirements
- 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
Tasks
- 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
Work Experience
approx. 4 - 6 years
Education
Bachelor's degreeORMaster's degree
Languages
English – Business Fluent
Tools & Technologies
AWSLinuxPostgreSQLNoSQLPythonJavaBashGitDockerKubernetesKafkaAmazon SagemakerDatabricksAirflowML FlowElastic SearchKibanaGrafanaTerraform
Benefits
Flexible Working
- •Flexible working hours
- •Hybrid work model
- •Home office days
Workation & Sabbatical
- •4-week annual work abroad
Learning & Development
- •Paid training days
Purpose-Driven Work
- •Paid volunteering days
Social Impact
- •Charity donation matching
Healthcare & Fitness
- •Health and fitness subsidy
Team Events
- •Frequent team events
- •Frequent social events
Informal Culture
- •Welcoming office environment
Snacks & Drinks
- •Complimentary coffee and refreshments
- •Fresh fruit and snacks
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of RepRisk AG 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
RepRisk AG
Industry
Other
Description
RepRisk is the world’s most respected Data as a Service (DaaS) company for reputational risks and responsible business conduct.
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