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.
Responsibilities
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
Dev Ops 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 (Fast API, 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 (Py Torch, 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 (v LLM, SGLang), distributed computing (Ray.io), and data labeling platforms (Label Studio)
Managed ML services (Sage Maker, 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
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
Technology, Information and Internet
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