Machine Learning Ops Engineer in Hatfield

Machine Learning Ops Engineer in Hatfield

Hatfield Full-Time 42000 - 84000 £ / year (est.) No home office possible
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Affinity Water Limited

At a Glance

  • Tasks: Operationalise machine learning, deploy models, and ensure system reliability.
  • Company: Affinity Water, a leader in sustainable water management.
  • Benefits: Competitive salary, flexible working, generous leave, and wellness support.
  • Why this job: Join a dynamic team and make a real impact in the water industry.
  • Qualifications: 5+ years in MLOps or DevOps, strong Python skills, and cloud experience.
  • Other info: Diverse and inclusive workplace with excellent career development opportunities.

The predicted salary is between 42000 - 84000 £ per year.

We are looking for a Machine Learning Ops Engineer to help operationalise machine learning across Affinity Water on a 24 month FTC. You will 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 Will 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 Are 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.
  • Life Assurance.

As a Disability Confident employer, we are committed to offering interviews to disabled candidates who meet the essential criteria and opt in on the application form. 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.

Machine Learning Ops Engineer in Hatfield employer: Affinity Water Limited

Affinity Water is an exceptional employer that prioritises employee growth and well-being, offering a supportive work culture where collaboration with data scientists and engineers leads to impactful projects in the water industry. With flexible working arrangements from the Hatfield office, generous benefits including a double match pension scheme, and a commitment to diversity and inclusion, employees can thrive both personally and professionally while contributing to meaningful advancements in machine learning operations.
Affinity Water Limited

Contact Detail:

Affinity Water Limited Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Ops Engineer in Hatfield

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your ML projects, especially those involving deployment pipelines and cloud services. This will give potential employers a taste of what you can do and set you apart from the crowd.

✨Tip Number 3

Prepare for interviews by brushing up on common MLOps scenarios. Be ready to discuss how you've tackled challenges in model monitoring and deployment. Practice makes perfect, so consider mock interviews with friends or mentors.

✨Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!

We think you need these skills to ace Machine Learning Ops Engineer in Hatfield

MLOps
DevOps
Machine Learning Lifecycle Management
Model Deployment
Model Monitoring
Model Maintenance
Python
ML Frameworks
Containerisation (Docker/Kubernetes)
CI/CD Pipelines
Cloud ML Services (AWS SageMaker)
Infrastructure-as-Code
Production-grade Linux Environments
API Services (Flask/Gunicorn)
Automated ML Pipelines

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Machine Learning Ops Engineer role. Highlight your experience with MLOps, CI/CD, and cloud services like AWS. We want to see how your skills match what we're looking for!

Showcase Your Projects: Include specific projects where you've built or maintained ML pipelines. We love seeing real-world examples of your work, especially if you can demonstrate how you’ve improved processes or solved problems.

Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for key achievements and avoid jargon unless it's relevant. We appreciate straightforward communication!

Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!

How to prepare for a job interview at Affinity Water Limited

✨Know Your Tech Stack

Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, Docker, Kubernetes, and AWS SageMaker. Brush up on your CI/CD pipeline knowledge and be ready to discuss how you've used these tools in past projects.

✨Showcase Your Problem-Solving Skills

Prepare examples of how you've tackled challenges in MLOps or DevOps roles. Think about specific incidents where you resolved issues with model performance or deployment. This will demonstrate your analytical skills and ability to think on your feet.

✨Understand the Business Impact

Be ready to discuss how machine learning can drive business value, particularly in the water industry. Show that you understand the importance of operational excellence and governance in ML processes, and how they contribute to overall business success.

✨Ask Insightful Questions

Prepare thoughtful questions about the team dynamics, current ML projects, and the company’s approach to MLOps. This not only shows your interest but also helps you gauge if the company culture aligns with your values and work style.

Machine Learning Ops Engineer in Hatfield
Affinity Water Limited
Location: Hatfield
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