At a Glance
- Tasks: Build and optimise automated ML deployment pipelines while collaborating with data scientists.
- Company: Join Affinity Water, a leader in operationalising machine learning.
- Benefits: Competitive salary, flexible working, generous leave, and wellbeing support.
- Other info: Dynamic team environment with excellent learning and development opportunities.
- Why this job: Make a real impact by deploying cutting-edge ML models in a supportive team.
- Qualifications: 5 years in MLOps or DevOps, strong Python skills, and experience with cloud services.
The predicted salary is between 60000 - 60000 £ per year.
Salary: £60,000 - £60,000 per year
Requirements:
- 5 years experience in MLOps, DevOps, or related roles
- Strong knowledge of ML lifecycle management, deployment, monitoring, and model maintenance
- Hands-on experience with Python and ML frameworks
- Experience with containerisation (Docker/Kubernetes)
- Proficiency in CI/CD pipelines and cloud ML services (AWS SageMaker preferred)
- Familiarity with infrastructure-as-code, production-grade Linux environments, and API services (Flask/Gunicorn)
- Ability to build automated, reliable ML pipelines with both structured and unstructured data
- Excellent problem-solving, analytical, and communication skills
- Self-motivated and organised
- Capability to embed best practices for governance, reproducibility, and operational excellence
- (Desirable) Experience with feature stores, model registries, real-time serving, and model retraining automation
- (Desirable) Integration of ML systems into business applications or APIs
- (Desirable) Exposure to Water Industry data, systems, and processes
Responsibilities:
- Build, maintain, and optimise automated ML deployment pipelines with CI/CD, containerisation, and orchestration
- Monitor model performance, data drift, and system health to ensure reliability and availability
- Support ML platforms and infrastructure both on-premise and in the cloud (AWS, SageMaker)
- Collaborate with data scientists to productionise models and embed ML Ops best practices across the organisation
- Ensure governance, compliance, documentation, and reproducibility of ML pipelines and models
- Provide 2nd/3rd line support, manage release cycles, and resolve incidents efficiently
- Continuously improve ML Ops processes, tooling, and automation for efficiency and reliability
Technologies:
- API
- AWS
- CI/CD
- Cloud
- DevOps
- Docker
- Flask
- Support
- Kubernetes
- Linux
- Machine Learning
- Python
- Security
We are looking for a Machine Learning Ops Engineer to help operationalise machine learning across Affinity Water on a 24 month FTC. Our team consists of data scientists, engineers, architects, and stakeholders, all focused on deploying, monitoring, and maintaining ML models in robust, scalable, and secure production environments. We offer a competitive salary starting from £60,000, flexible working arrangements at our Hatfield office, and various learning and development opportunities. Our comprehensive benefits package includes annual leave increasing with service, a generous pension scheme, family leave benefits, and wellbeing support, all aimed at ensuring a positive work environment for our team.
Machine Learning Ops Engineer in London employer: Affinity Water Limited
Affinity Water is an exceptional employer, offering a dynamic work culture that prioritises collaboration and innovation in the field of machine learning. Located in Hatfield, our team enjoys flexible working arrangements, a competitive salary, and a comprehensive benefits package that includes generous annual leave, a robust pension scheme, and dedicated wellbeing support, all designed to foster employee growth and satisfaction.
