Senior MLOPS

Complexio; City Of London; Remote; GBP 50,000 - 80,000; Full time

Job summary

A leading AI platforms provider in the UK is seeking a versatile MLOps Engineer to bridge the gap between research and production systems. The role involves designing and maintaining ML pipelines, managing cloud infrastructure, and collaborating with research teams. Candidates should have strong Python skills, cloud experience, and an understanding of MLOps tools. This is a remote-first opportunity with a focus on innovative AI automation.

Benefits

Work with a groundbreaking AI platform

Remote-first working environment

Influence product direction in a fast-scaling company

Qualifications

• Advanced Python programming with production experience; familiarity with web frameworks (FastAPI, Flask), testing, and ML libraries is a plus.
• Cloud computing expertise across major platforms with hands-on experience in Kubernetes services and managed ML services.
• Experience collaborating with data science teams to translate experimental models into production systems.
• Strong software engineering foundations including version control and testing strategies.

Responsibilities

• Design, build, and maintain end-to-end ML pipelines from data ingestion to model deployment and monitoring.
• Architect and manage scalable cloud infrastructure for ML workloads.
• Partner closely with data scientists to translate models into production-ready systems.
• Establish infrastructure as code, CI/CD pipelines, and comprehensive logging/monitoring.
• Production Python experience with web frameworks, testing frameworks, and ML libraries is a great-to-have.

Skills

Advanced Python programming

Cloud computing expertise

Collaboration with data science teams

MLOps tools experience

Software engineering foundations

Tools

AWS

GCP

Azure

Kubernetes

Docker

MLflow

Kubeflow

PyTorch

scikit-learn

numpy

Job description

Overview

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.

We are seeking a versatile MLOps Engineer to bridge the gap between data science research and production-ready machine learning systems. This role requires a complete engineering skillset spanning Python development, cloud infrastructure, and collaborative work with research teams.

We\'re looking for a complete engineer who can seamlessly transition between writing production Python code, designing cloud architectures, and collaborating with researchers on cutting-edge ML projects. You should be equally comfortable debugging a Kubernetes deployment, optimising a training pipeline, and explaining technical trade-offs to data scientists.

Responsibilities

• Production ML Pipeline Development: Design, build, and maintain end-to-end ML pipelines from data ingestion to model deployment and monitoring
• Infrastructure Management: Architect and manage scalable cloud infrastructure for ML 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
• Advanced Python Programming: Production Python experience with web frameworks (FastAPI, Flask), testing frameworks, and ML libraries (PyTorch, scikit-learn, numpy) a great-to-have
• Cloud Computing Expertise: Hands-on experience with major cloud platforms (AWS, GCP, or Azure), including Kubernetes services (EKS/GKE/AKS) and managed ML services (SageMaker, Vertex AI)
• Research Team Collaboration: Experience working with data science or research teams, effectively translating experimental code into production systems
• 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)
• Software Engineering: Strong foundation in version control, testing strategies, software architecture principles, async programming, and concurrent system design

Benefits

• Work with a groundbreaking AI platform solving real enterprise pain points
• Help clients achieve measurable ROI through next-gen automation
• Join a remote-first, globally distributed team backed by industry leaders
• Shape the success function and influence product direction in a fast-scaling AI company

Qualifications

• Advanced Python programming with production experience; familiarity with web frameworks (FastAPI, Flask), testing, and ML libraries (PyTorch, scikit-learn, numpy) is a plus
• Cloud computing expertise across major platforms (AWS, GCP, Azure) with hands-on experience in Kubernetes services (EKS, GKE, AKS) and managed ML services (SageMaker, Vertex AI)
• Experience collaborating with data science or research teams and translating experimental models into production systems
• Experience with MLOps tools (MLflow, Kubeflow), container technologies (Docker, Kubernetes), inference engines (vLLM, SGLang), distributed computing (Ray.io), and data labeling platforms (Label Studio)
• Strong software engineering foundations: version control, testing strategies, software architecture, async programming, and concurrent design