Requirements:

• Documented experience in implementing and monitoring machine learning models in production environments,
• Minimum of 5 years experience working with Docker, Kubernetes, Helm, and CI/CD pipelines,
• At least 5 years of experience with monitoring tools such as Prometheus, Thanos, or Grafana,
• Familiarity with model monitoring tools such as Arize, Evidently AI, or Alibi Detect,
• Experience in conducting A/B tests and working with service mesh software (e.g., Istio),
• Proficiency in using platforms like Kubeflow or OpenDataHub for deploying and managing models,
• Very good understanding of infrastructure monitoring concepts and best practices in this area,
• Excellent problem-solving skills and diagnosing complex technical issues,
• Experience working with cloud platforms (AWS OR Google Cloud Platform OR Azure),
• Knowledge of scripting languages and automation (e.g., Bash, Python).
• Proficiency in English enabling fluent communication both verbally and in writing.

Responsibilities:

• Deploying machine learning models to production environments,
• Monitoring the performance of models in real-time,
• Creating and maintaining CI/CD pipelines,
• Configuring and managing Docker containers and Kubernetes clusters,
• Setting up and expanding system monitoring using tools like Prometheus, Thanos, Grafana,
• Implementing A/B testing and integrating with service mesh (e.g. Istio),
• Working with model management platforms such as Kubeflow and OpenDataHub,
• Automating tasks using scripts (e.g. Bash, Python),
• Resolving technical issues and optimizing system performance,
• Collaborating with Data Science, DevOps, and engineering teams to ensure deployment stability.

We offer:

• paid leave
• Work in an international environment - permanent - all work in an English-speaking environment