Lead MLOps

February 18

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Complexio

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Complexio is a company specializing in foundational artificial intelligence solutions designed for task automation using whole company data. Headquartered in London, they also have offices in Copenhagen and Monaco. Complexio is focused on leveraging AI technologies to enhance efficiency and automate processes within organizations. They prioritize data privacy and consent management, ensuring compliance with international data protection standards.

11 - 50 employees

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

📋 Description

• Complexio’s Foundational AI automates business activities by ingesting structured and unstructured company-wide data to extract meaningful insights. • Our proprietary models and algorithms analyse human interactions with data, enabling automation to replicate and enhance these processes independently. • We are looking for an MLOps Engineer to design, deploy, and optimize machine learning infrastructure across on-premises and multi-cloud environments (AWS, Azure, Google Cloud). • You will be responsible for ensuring the smooth deployment, monitoring, and scaling of AI/ML models while managing data pipelines and GPU-powered workloads. • Key Responsibilities • Deploy and manage ML models in production environments, ensuring scalability and reliability. • Design and maintain ML pipelines, automating training, validation, and deployment workflows. • Optimize AI/ML infrastructure for performance, cost, and efficiency across cloud and on-premise systems. • Integrate and manage vector and graph databases (e.g., Neo4j, Pinecone, Milvus) for AI-driven applications. • Implement observability & monitoring solutions for model performance, data drift, and system health. • Ensure compliance with security and data governance best practices in ML deployment. • Collaborate with Data Scientists and DevOps teams to streamline AI model lifecycle management.

🎯 Requirements

• Experience: 7+ years in ML infrastructure, DevOps, or Cloud Engineering. • ML & Cloud Stack: • Hands-on experience with Kubernetes, Docker, and containerised ML workloads. • Strong expertise in AWS, Azure, or Google Cloud, with knowledge of GPU-based computing. • Experience in CI/CD pipelines for machine learning (e.g., GitHub Actions, MLflow, Kubeflow). • Programming: • Proficiency in Python (experience with Go or Java is a plus). • Strong experience in scripting & automation (Bash, Terraform, Ansible). • Databases & Storage: • Knowledge of vector & graph databases (e.g., Neo4j, Milvus, Pinecone). • Experience managing distributed data storage & processing. • Bonus Points • Experience deploying LLMs & NLP models in production. • Familiarity with feature stores and model versioning. • Experience with edge AI deployments and federated learning.

🏖️ 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. • (Remote must be within 4-5 hours of CET timezone)