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Urgent! MLOps Engineer Position in Warsaw - Complexio



Job description

Complexio’s Foundational AI platform automates business processes by ingesting and understanding complete enterprise data—both structured and unstructured.

Through proprietary models, knowledge graphs, and orchestration layers, Complexio maps human-computer interactions and autonomously executes complex workflows at scale.

Established as a joint venture between Hafnia and Símbolo—with partners including Marfin Management, C Transport Maritime, BW Epic Kosan, and Trans Sea Transport—Complexio is redefining enterprise productivity through context-aware, privacy-first automation.

  • Infrastructure Management: Architect and manage scalable cloud infrastructure workloads, including container orchestration and automated testing.
  • Research Collaboration: Partner closely with data scientists and research teams to translate experimental models into robust, production-ready systems.
  • DevOps Best Practices: Establish infrastructure as code, CI/CD pipelines, automated deployments, and comprehensive logging/monitoring.

Requirements

Qualifications

  • 5+ years of experience after completing higher education.
  • Advanced Python Programming: Production Python experience with web frameworks (FastAPI, Flask), testing frameworks,
  • Cloud Computing Expertise: Hands-on experience with major cloud platforms (AWS, GCP, or Azure), including Kubernetes services (EKS/GKE/AKS).
  • Research Team Collaboration: Experience working with data science or research teams, effectively translating experimental code into production systems.
  • Software Engineering: Strong foundation in version control, testing strategies, software architecture principles, async programming, and concurrent system design.
  • Data Infrastructure: Design and implement scalable data infrastructure solutions leveraging distributed computing frameworks like Apache Spark or similar for large-scale data processing.

    Build and optimize data lake architectures to support analytics, ensuring high performance, reliability, and data governance across large datasets.
  • ML experience not required, but you should know why you want to work in this field.
  • English min B2.

 

Nice to have

  • ML libraries (PyTorch, scikit-learn, numpy).
  • Production ML Pipeline Development: Design, build, and maintain end-to-end ML pipelines from data ingestion to model deployment and monitoring.
  • ML Infrastructure: Experience with MLOps tools (MLflow, Kubeflow), container technologies (Docker, Kubernetes), inference engines (vLLM, SGLang), distributed computing (Ray.io), and data labeling platforms (Label Studio).
  • Managed ML services (SageMaker, Vertex AI.

Benefits

  • Join a pioneering joint venture at the intersection of AI and industry transformation.
  • Work with a diverse and collaborative team of experts from various disciplines.
  • Opportunity for professional growth and continuous learning in a dynamic field.


Required Skill Profession

Computer Occupations



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