Lead MLOps Engineer
Lviv, Ukraine
4 дня назад


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.

We are the Data Science Center of Excellence and you will have a chance to contribute to a wide range of projects from different areas and technologies.

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


  • A Machine Learning Engineer interested in operationalizing ML pipelines and bringing them to production
  • Able to design and implement ML end-to-end solutions, create data pipelines and architectures, set up the infrastructure, and optimize existing models
  • Strongly competent in software engineering, have a solid knowledge of Machine Learning / Deep Learning models and workflows, 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
  • 4+ years of relevant background as ML Engineer or similar
  • Solution architecture design and ability to articulate complex architectures to a non-technical audience
  • Being hands-on in ML operationalization
  • Strong knowledge of Python and traditional Python DS / ML stack
  • Container technology and orchestration platforms such as Kubernetes
  • Knowledge of any major cloud platform such as GCP, AWS, Azure, or IBM
  • CI / CD / CT pipelines
  • Strong requirements gathering and estimation
  • Upper-Intermediate English level or higher
  • Your extra power reveals in the following experience

  • Being hands-on with Kubeflow, MLflow, or similar
  • AI Platform, AI Platform Pipelines / Kubeflow, Google AutoML
  • Hadoop ecosystem and Apache Spark
  • Workflow orchestration platforms such as Airflow
  • Cloud IAM, Stackdriver, NumPy / Pandas / sklearn / TensorFlow
  • Designing and building feature stores
  • Message queues and streaming platforms
  • R, Java / Scala, Julia

  • 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
  • Work 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
  • Design and implement automated deployment and integration of ML models
  • Set up 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
  • 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
  • Have access to 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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