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Machine Learning Engineer(m/w/x)
Building and optimizing search engines with ML features and LLMs for reputational risk data. Expert-level Python and SQL skills required. 4 weeks work abroad, flexible hours.
Requirements
- Master's degree in Computer Science, Engineering, Statistics, or related STEM field
- 3+ years of hands-on ML Engineer experience in production
- Expert-level Python skills
- Solid proficiency in SQL
- Developing and deploying NLP models
- Developing and deploying information retrieval systems
- Developing and deploying search engines
- Integrating AI and LLMs into ML pipelines
- Software engineering best practices
- Clean, maintainable, scalable code
- Cloud platforms experience
- CI/CD workflows experience
- Containerized environments experience
- Proactive mindset
- Ability to take ownership
- Ability to drive solutions forward
- Strong analytical thinking
- Structured problem-solving
- Highly efficient execution
- Excellent communication skills
- Fluency in English
- Experience in low-code languages like C++ or Java
- Experience with AWS, particularly SageMaker
- Prior experience fine-tuning LLMs
- Prior experience training LLMs
- Building and managing data pipelines
- Valid work permit
Tasks
- Design and implement ML features
- Build and optimize multifaceted search engines
- Develop, integrate, and maintain microservices
- Apply advancements in ML and LLMs
- Train, evaluate, and optimize models
- Collaborate with ML engineers, backend engineers, and product owners
- Contribute to a well-balanced tech stack
- Ensure clean, high-quality code
- Participate in Agile/Scrum processes
Work Experience
- 3 years
Education
- Master's degree
Languages
- English – Fluent
Tools & Technologies
- Python
- SQL
- NLP
- AI
- LLMs
- AWS
- SageMaker
- C++
- Java
Benefits
Flexible Working
- Flexible working hours
- Hybrid work model
Workation & Sabbatical
- 4 weeks work abroad
Learning & Development
- Paid training days
Purpose-Driven Work
- Paid volunteering days
Social Impact
- Charity donation matching
Healthcare & Fitness
- Health & fitness subsidy
Team Events
- Team and social events
Snacks & Drinks
- Complimentary coffee and refreshments
- Complimentary fruit and snacks
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Machine Learning Engineer(m/w/x)
Building and optimizing search engines with ML features and LLMs for reputational risk data. Expert-level Python and SQL skills required. 4 weeks work abroad, flexible hours.
Requirements
- Master's degree in Computer Science, Engineering, Statistics, or related STEM field
- 3+ years of hands-on ML Engineer experience in production
- Expert-level Python skills
- Solid proficiency in SQL
- Developing and deploying NLP models
- Developing and deploying information retrieval systems
- Developing and deploying search engines
- Integrating AI and LLMs into ML pipelines
- Software engineering best practices
- Clean, maintainable, scalable code
- Cloud platforms experience
- CI/CD workflows experience
- Containerized environments experience
- Proactive mindset
- Ability to take ownership
- Ability to drive solutions forward
- Strong analytical thinking
- Structured problem-solving
- Highly efficient execution
- Excellent communication skills
- Fluency in English
- Experience in low-code languages like C++ or Java
- Experience with AWS, particularly SageMaker
- Prior experience fine-tuning LLMs
- Prior experience training LLMs
- Building and managing data pipelines
- Valid work permit
Tasks
- Design and implement ML features
- Build and optimize multifaceted search engines
- Develop, integrate, and maintain microservices
- Apply advancements in ML and LLMs
- Train, evaluate, and optimize models
- Collaborate with ML engineers, backend engineers, and product owners
- Contribute to a well-balanced tech stack
- Ensure clean, high-quality code
- Participate in Agile/Scrum processes
Work Experience
- 3 years
Education
- Master's degree
Languages
- English – Fluent
Tools & Technologies
- Python
- SQL
- NLP
- AI
- LLMs
- AWS
- SageMaker
- C++
- Java
Benefits
Flexible Working
- Flexible working hours
- Hybrid work model
Workation & Sabbatical
- 4 weeks work abroad
Learning & Development
- Paid training days
Purpose-Driven Work
- Paid volunteering days
Social Impact
- Charity donation matching
Healthcare & Fitness
- Health & fitness subsidy
Team Events
- Team and social events
Snacks & Drinks
- Complimentary coffee and refreshments
- Complimentary fruit and snacks
About the Company
RepRisk AG
Industry
IT
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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