Senior Machine Learning Platform Engineer

RepRisk AG

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profile Job Location:

Berlin - Germany

profile Monthly Salary: Not Disclosed
Posted on: 4 hours ago
Vacancies: 1 Vacancy

Job Summary

About You 

Are you looking to apply your strong data and/or platform engineering skills to real-world problems and help keep companies around the globe transparent and accountable for their business conduct Do you want to be part of a growing team of ML experts in shaping a state-of-the-art Natural Language Processing pipeline including LLM  models Are you someone who prefers working for an agile growing firm where you can make a real contribution and be involved in a variety of tasks but without the uncertainty of a start-up 

If your answers are YES then this is the perfect role for you! 

Your Responsibilities 

As our ML Platform Engineer you will work daily with the Machine Learning team based in Zürich Switzerland to build maintain and expand the full machine learning and data pipeline within RepRisk. You will be:  

  • Support the development of feature pipelines automated data creation ETL pipelines and manage the underlying infrastructure and applications 
  • Helping to design test deploy monitor as well as maintain production-scale ML models and model endpoints primarily in natural language processing. 
  • Design implement and monitor the CI/CD pipelines and cloud infrastructure for cutting-edge ML applications with efficiency performance and cost optimization in mind. 
  • Manage the lifecycle access and deployment of LLM models for production applications and ad-hoc testing by developers 

Qualifications :

We are looking for candidates with a strong background in data and platform engineering. If you only have experience with data or platform engineering we would still be happy to consider your application. 

You Bring 

  • Experience designing building and deploying cloud-based solution architectures and distributed systems primarily on AWS 
  • Experience setting up and maintaining data and ML pipelines 
  • Experience with implementing CI/CD pipelines using best practices. 
  • Experience with Data Warehousing technologies 
  • Experience with LLM management and agentic AI deployment patterns 
  • System software and management systems experience in Linux environment (Network Management Systems Management Datacenter Automation) 
  • Experience with PostgreSQL database architectures and queries; experience with NoSQL would be a plus 
  • Strong Python skills: working knowledge of Java or Bash would be a plus 
  • Knowledge of Git Docker Kubernetes Kafka and experience with Amazon Sagemaker Databricks Airflow ML Flow Elastic Search Kibana Grafana Terraform (or similar) would be a plus 
  • Working experience in debugging to diagnose computational bottlenecks and in troubleshooting issues and software testing 
  • Analytical and structured thinking organizational skills solution-oriented and efficiency 
  • Strong communication skills with proficiency in English every other language is a plus 

Additional Information :

Please note that we will only consider candidates with a valid work permit. 


Remote Work :

No


Employment Type :

Full-time

About You Are you looking to apply your strong data and/or platform engineering skills to real-world problems and help keep companies around the globe transparent and accountable for their business conduct Do you want to be part of a growing team of ML experts in shaping a state-of-the-art Natural L...
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Key Skills

  • Industrial Maintenance
  • Machining
  • Mechanical Knowledge
  • CNC
  • Precision Measuring Instruments
  • Schematics
  • Maintenance
  • Hydraulics
  • Plastics Injection Molding
  • Programmable Logic Controllers
  • Manufacturing
  • Troubleshooting

About Company

About Us RepRisk is a rapidly growing global company and a pioneer in the ESG data science field. Our goal is to make the world a better place by creating transparency in the business world – we are driving positive change via the power of data. We combine AI and machine learning with ... View more

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