Machine Learning Ops Engineer
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We are looking for a Machine Learning Ops Engineer to help operationalise machine learning across Affinity Water on a 24 month FTC. You’ll work with data scientists, engineers, architects, and stakeholders to deploy, monitor, and maintain ML models in robust, scalable, and secure production environments, turning advanced analytics into sustained business value.
What You’ll Do
- 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 on-premise or in the cloud (AWS, SageMaker), ensuring scalability and security.
- 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.
What We’re Looking For
Essential:
- 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), containerisation (Docker/Kubernetes), CI/CD pipelines, and cloud ML services (AWS SageMaker preferred).
- Experience with infrastructure-as-code, production-grade Linux environments, and API services (Flask/Gunicorn).
- Proficiency in building automated, reliable ML pipelines with structured and unstructured data.
- Excellent problem-solving, analytical, and communication skills; self-motivated and organised.
- Ability to embed best practices for governance, reproducibility, and operational excellence.
Desirable:
- Experience with feature stores, model registries, real-time serving, and model retraining automation.
- Integration of ML systems into business applications or APIs.
- Exposure to Water Industry data, systems, and processes.
Benefits:
- Salary: From £60,000 dependant on skills and experience
- Able to work from the Hatfield office at least 2 days per week, with flexibility to spend additional days on-site as required by the programme
- Learning and development opportunities, including mentoring and a range of formal courses and open learning resources.
- Entry into the company annual bonus scheme
- Annual leave from 26-30 rising with length of service, and the option to purchase up to 5 extra days.
- A ‘Celebration Day’ in addition to public holidays that people can use to celebrate a religious festival or other occasion that is important to them.
- A generous 'double match pension scheme' that doubles the contributions you make (company contribution capped at 12%)
- We offer a range of family benefits including enhanced Maternity, Adoption, Paternity, Shared Parental Leave, Fertility Support Leave and up to 5 full or 10 half days of paid Carers Leave.
- Menopause policy and Reasonable Adjustment policy to help everyone perform at their best.
- Access to our Wellbeing Centre with support for looking after your physical and mental health.
- Discounts at a Range of Retail Outlets and on Dental and Medical Insurance through our Tap4Perks scheme.
- Up to 4 Affinity days a year to volunteer in the community.
Disability Confident
As a Disability Confident employer, we’re committed to offering interviews to disabled candidates who meet the essential criteria and opt in on the application form. Ask the Talent Acquisition lead for the full job description to see all the criteria. If we have a very high volume of applicants and we’re not able to offer interviews to all, we’ll take a fair and proportionate number of disabled candidates through.
Affinity Water recognises the benefits of greater diversity in our workforce to better reflect the communities we serve. We are committed to building a more inclusive culture where every member of our workforce can thrive.