Senior MLOps Engineer
Krakow, Poland
2 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!


A Machine Learning Engineer who is interested in operationalizing ML pipelines and bringing them to production. You will design and implement ML end-to-end solutions, create data pipelines and architectures, set up the infrastructure, and optimize existing models.

You should be strongly competent in Machine Learning / Deep Learning models and model lifecycle, have a solid knowledge of software engineering, and a good understanding of DevOps / MLOps principles.

A candidate should demonstrate such experience and abilities as

  • MS degree in computer science or related field 3+ years of relevant experience
  • Strong knowledge of Python and traditional Python DS / ML stack
  • Solid knowledge of ML solutions design patterns
  • Working knowledge of AI / ML and Data Engineering tools in any major cloud platform such as GCP, AWS or Azure
  • Hands-on experience with ML operationalization
  • Experience in setting up CI / CD / CT pipelines for ML
  • Hands-on experience with Kubeflow, MLflow, or similar
  • Working experience with containers and container orchestration platforms such as Kubernetes
  • Upper-Intermediate English level or higher
  • Strong requirements gathering and estimation
  • Your extra power is having experience with

  • Designing and building feature stores
  • Hadoop ecosystem and Apache Spark
  • Workflow orchestration platforms such as Airflow
  • Message queues and streaming platforms
  • Java / Scala

  • Communicate use cases, requirements, and expectations with stakeholders
  • Guide Engineering and Data Science teams on ML systems production lifecycle
  • Collaborate with Data Science teams on model operationalization strategies
  • Work closely with Product teams to deliver and operate ML systems
  • 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, and system monitoring
  • Set up scalable monitoring systems for data pipelines and ML models

  • Operationalize our clients’ AI solutions by leveraging best practices in Machine Learning and MLOps, DevOps, and Software engineering
  • 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
  • Participate in international events
  • Get certifications in cutting-edge technologies
  • Have the possibility to work with the latest modern tools and technologies on different projects
  • Access strong educational and mentorship programs
  • Communicate with the world-leading companies from our logos portfolio
  • Work as a consultant on different projects with a flexible schedule
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