Machine Learning Engineer / MLOps Engineer

• Design, build, and maintain end-to-end machine learning pipelines, from data ingestion and model training through to deployment and monitoring.
• Deploy, operate, and optimise machine learning models in production environments, ensuring reliability, scalability, and performance.
• Develop scalable data pipelines supporting both batch and real-time machine learning workloads.
• Build and improve ML infrastructure, automation, CI/CD processes, and operational tooling.
• Collaborate closely with data scientists to productionise machine learning models and translate research into robust production systems.
• Partner with software engineers to integrate ML services into larger backend platforms and applications.
• Contribute to cloud-native ML platforms using containerisation and orchestration technologies.
• Drive continuous improvements to system architecture, observability, performance, and engineering best practices.
• Document workflows, infrastructure, and technical solutions while sharing knowledge across the engineering team.

• Several years of professional experience developing and operating production machine learning systems.
• Strong Python programming skills with experience using frameworks such as PyTorch, TensorFlow, or JAX.
• Experience deploying and managing ML models throughout the complete machine learning lifecycle.
• Strong background building scalable data pipelines using technologies such as Apache Spark, Airflow, Prefect, or similar tools.
• Experience working with cloud platforms including AWS, Azure, or Google Cloud Platform.
• Good knowledge of Docker, Kubernetes, CI/CD pipelines, and infrastructure automation.
• Familiarity with distributed systems and designing scalable, reliable software architectures.
• Experience collaborating across multidisciplinary engineering teams.
• You're ambitious, invested in the company's long-term success, and eager to grow from a senior engineering role into a future technical leadership or management position.
• Excellent analytical thinking, problem-solving abilities, and communication skills.

Ideally, you will also bring experience with one or more of the following:

• Distributed training or GPU-accelerated machine learning.
• Performance optimisation for model training or inference.
• Streaming or real-time data processing.

• Reinforcement learning, explainable AI, transfer learning, or other advanced ML techniques.
• Opportunity to work on cutting-edge machine learning solutions with real-world impact.
• Join a collaborative team of experienced engineers, data scientists, and technical specialists.
• Work with modern cloud-native technologies and industry-leading ML tooling.
• Excellent opportunities for professional development and technical growth.
• Flexible working environment with a strong engineering culture focused on innovation and continuous improvement.

If you're passionate about building scalable, production-ready machine learning systems and want to make a meaningful impact, we'd love to hear from you.

full_time