Senior Mlops Engineer

Talon.One

Berlin, Germany
Not specified; benefits: €1,000 annual learning bu...
On-site
6+ years software engineering experience
3+ years mlops or ml infrastructure
Python programming and ml frameworks
Talon.One is seeking a Senior MLOps Engineer to join their team in Berlin, where you'll develop and maintain MLOps infrastructure to support machine learning model deployment and monitoring. The role emphasizes collaboration with data scientists and engineers, requiring strong technical skills in MLOps, cloud platforms, and programming

Job Summary

  • The role involves designing robust MLOps infrastructure to support the deployment and scalability of machine learning models within a cross-functional Intelligence Tribe.
  • Candidates will implement CI/CD workflows for ML models to ensure reproducibility, reliability, and version control while collaborating with data scientists and engineers.
  • The company offers a comprehensive benefits package including a €1,000 annual learning budget, 30 days of annual leave, and a monthly home office allowance.

Matching Summary

Match Score: 85

Talon.One is seeking a Senior MLOps Engineer to join their team in Berlin, where you'll develop and maintain MLOps infrastructure to support machine learning model deployment and monitoring. The role emphasizes collaboration with data scientists and engineers, requiring strong technical skills in MLOps, cloud platforms, and programming.

Salary

Not specified; Benefits: €1,000 annual learning budget; 30 days annual leave; Home office setup budget and allowance

Skills & Requirements

Must-have

  • 6+ years software engineering experience
  • 3+ years MLOps or ML infrastructure
  • Python programming and ML frameworks
  • Google Cloud Platform and Terraform
  • Docker and Kubernetes orchestration
  • CI/CD implementation for ML models
  • Model monitoring and data drift detection

Nice-to-have

  • Experience with Vertex AI or SageMaker
  • Knowledge of MLflow or Kubeflow
  • Background in Airflow pipeline management
  • Familiarity with blue-green deployment strategies
  • Understanding of ethical AI guidelines
  • Experience in high-availability real-time environments

Key Requirements

  • 6+ years software engineering or DevOps experience
  • 3+ years in MLOps or ML infrastructure roles
  • Strong proficiency in Python programming
  • Hands-on experience with GCP and Terraform
  • Expertise in Docker and Kubernetes technologies

Work Rights

Not specified

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