About the Company

We are an innovative technology organisation developing scalable AI-powered products and intelligent decision systems for European markets. Our teams combine machine learning research, cloud infrastructure, and software engineering to deliver production-grade solutions that support automation, predictive analytics, and business optimisation.

Role Overview

We are seeking a Senior Machine Learning Engineer to lead the design and implementation of production machine learning systems and reusable ML platform components. You will take ownership of the engineering lifecycle, from model architecture and experimentation to serving, monitoring, optimisation, and ongoing maintenance.

This role is suited to an experienced engineer who can bridge data science and software engineering, establish reliable ML development practices, and guide technical decisions across multidisciplinary teams.

Key Responsibilities

• Design and implement scalable machine learning systems for predictive analytics, recommendation, classification, and other business applications.
• Lead the transition of experimental models into reliable, maintainable production services.
• Build reusable components for model training, feature processing, inference, and deployment.
• Design batch and real-time inference architectures to support diverse application requirements.
• Establish MLOps standards for experiment tracking, model versioning, automated testing, and deployment.
• Optimise model performance, inference latency, memory usage, and infrastructure costs.
• Implement monitoring and alerting for model quality, data drift, service reliability, and prediction performance.
• Collaborate with data engineers to develop dependable training and feature pipelines.
• Work with platform and DevOps teams to improve deployment automation and infrastructure scalability.
• Lead technical reviews and establish best practices for machine learning software development.
• Mentor junior engineers and support the professional development of the wider team.
• Evaluate emerging ML frameworks and infrastructure technologies for practical adoption.
• Ensure machine learning solutions incorporate appropriate security, explainability, documentation, and responsible AI controls.

Requirements and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Mathematics, Engineering, or a related field, or equivalent professional experience.
• At least 5 years of experience in machine learning engineering, software engineering, or production AI systems.
• Advanced Python skills and strong software design fundamentals.
• Experience with PyTorch, TensorFlow, scikit-learn, or comparable machine learning frameworks.
• Demonstrated experience deploying and maintaining machine learning models in production.
• Strong understanding of model evaluation, feature engineering, experiment management, and inference optimisation.
• Experience with Docker, Kubernetes, CI/CD pipelines, and cloud infrastructure.
• Practical knowledge of MLOps tools such as MLflow, Kubeflow, or equivalent platforms.
• Experience with distributed data processing, model-serving APIs, and monitoring systems.
• Familiarity with infrastructure as code, automated testing, and production incident management.
• Ability to lead technical projects, mentor colleagues, and communicate complex engineering concepts clearly.
• Knowledge of model governance, data privacy, and responsible AI principles is an advantage.

What We Offer

• Competitive salary package reflecting seniority and technical expertise.
• Flexible hybrid or remote working arrangements, subject to business requirements.
• Technical ownership of high-impact production machine learning systems.
• Access to modern cloud infrastructure and advanced AI engineering tools.
• Opportunities to shape platform architecture and engineering standards.
• Professional development and opportunities to lead technical initiatives.
• A collaborative international environment with strong engineering practices.
• Career progression within a growing AI-focused organisation.

Application Instructions

Candidates should submit an up-to-date CV highlighting production machine learning systems, MLOps implementations, and software architecture experience. Please include examples of models or ML platforms you have built, deployed, or scaled, together with your specific technical contributions.

Lead the engineering of scalable machine learning platforms and turn advanced AI capabilities into dependable production services.

Are you interested in this position?

Apply by clicking on the “Apply Now” Button below!

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