Senior MLOps Engineer
Wroclaw, Poland
3 d. temu


Transforming the way thousands of global organizations do business by developing the most innovative technologies and processes in Big Data, Internet of Things (IoT), Data Science, and Experience Design.

We are one of the largest teams in Eastern Europe that stood at the origins of Data Science, so you will get tons of experience while working with the best talents in the field.

In a Data Science Center of Excellence, you will have a chance to contribute to a wide range of projects in different areas and technologies.

We are looking for a person who is inspired by data, analytics, and AI as much as we are, and who wants to grow with us!


  • MLOps Engineer with MS degree in computer science or related field and 4+ years of relevant experience
  • Experienced with solution infrastructure design
  • Familiar with the Data Science systems and workflow, esp. with all aspects around model operationalization
  • Proficient in distributed systems principles
  • Expertised with engineering best practices, including analyzing, designing, developing, deploying, and supporting solution infrastructure implementations and upgrades
  • Skilled in building and using data systems at scale
  • Experient in GCP, AWS, or Azure beyond basic provisioning, especially data pipeline components, CI / CD, k8s, and ML-relevant managed services
  • Showing a mastery of container technology and orchestration platforms using Kubernetes
  • Proficient in building CI / CD pipelines using Gitlab, Jenkins, Azure DevOps, Google Cloud Build, or similar
  • Able to perform high-quality performance analysis
  • Skilled in Python, SQL, and Shell scripting
  • Practiced in Networking, TCP / IP, and Linux administration
  • Strong in requirement gathering and estimation
  • Capable of articulating complex architecture to non-technical audiences
  • Able to recognize Data Mining / Machine Learning workflow patterns and solutions associated with those patterns
  • The one who possesses excellent organization, time-management, presentation, and communication skills
  • Demonstrating Upper-Intermediate English level or higher (oral / written)
  • Your extra power reveals in the following experience

  • Kubeflow, MLFlow, Argo Workflows
  • Workflow management platforms such as Airflow
  • Databases and object stores such as PostgreSQL, Redshift, Athena, BigQuery, S3 or similar
  • Storage design Knowledge of Java / Scala
  • Hadoop ecosystem, Apache Spark or similar
  • Stream processing platforms such as Apache Kafka, Cloud Pub / Sub
  • Developing solutions using automation tools such as Terraform, Ansible, Chef
  • Visualization platforms such as Tableau
  • Proficiency with monitoring tools such as Grafana, Prometheus, Stackdriver, Zabbix
  • A concept of GitOps approach and tools

    Your duties will enable you to

  • Communicate with stakeholders to identify use cases, gather requirements, and set up expectations
  • Guide Engineering and Data Science teams on ML systems production lifecycle
  • Educate Product teams on best practices for putting ML systems in production
  • Collaborate with Data Science teams on model operationalization strategies
  • Cooperate closely with Product teams to deliver and operate ML systems
  • Design and implement end-to-end production pipelines for ML solutions
  • Support and continuously enhance ML software infrastructure : CI / CD, data stores, cloud services, network configuration, security, system monitoring, etc.
  • Design and implement automated deployment and integration of ML models
  • Setup scalable monitoring systems for data pipelines and ML models
  • Maintain ML pipelines in production

  • Operationalize our clients’ AI solutions by leveraging best practices in DevOps, Machine Learning and Solution Architecture
  • Maintain synergy of Data Scientists, DevOps team, and ML Engineers to build infrastructure, set up processes, productize machine learning pipelines, and integrate them into existing business environments
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