Designing, developing, and implementing machine learning models and algorithms at PayPal. Collaborating with data scientists and software engineers to enhance services through innovative AI/ML solutions.
About the role
- Machine Learning Ops Engineer deploying and optimizing ML models at Affinity Water. Collaborating with teams to enhance the reliability of analytics solutions.
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 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.
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), 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
- 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.
- Life Assurance.
- 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.
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