National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Machine Learning Operations (ML Ops) Engineer

Drax
Immingham
1 day ago
Create job alert

Machine Learning Operations (MLOps) Engineer

The full job description covers all associated skills, previous experience, and any qualifications that applicants are expected to have.
Flexible Location – Ipswich, London or Selby
Permanent, full time

Closing date - 2 July 2025

Who we are

We’re not just talking about making a difference, we’re making it happen. We generate dispatchable, renewable power and create stable energy in an uncertain world. Building on our proud heritage, we have ambition to become the global leader in sustainable biomass and carbon removals.

You’ll be joining our teams of practical doers, future thinkers and business champions. We’re enabling a zero carbon, lower cost energy future for all, and working hard to decarbonise the planet for generations to come.

About the role

As a Machine Learning Operations (MLOps) Engineer, you’ll be responsible for managing, releasing and monitoring Machine Learning (ML) and Artificial Intelligence (AI) artefacts using automated frameworks. You’ll also optimise ML/AI code written by our Data Scientists into Production-ready software according to agreed performance and cost criteria.

You’ll play a key role ensuring that ML/AI projects are setup for success via the automation of residual manual steps in the development and production lifecycle. You’ll also provide essential insights into the ongoing predictive capability and cost of deployed ML/AI assets using language and visualisations appropriate for your audience.

It’s an opportunity to work across multiple projects concurrently. You’ll use your judgement to determine which projects and teams need most of your time. You’ll contribute to early engagements through strong communication skills, domain experience and knowledge gathered throughout your career.

This role requires you to have adept time-management and prioritisation skills to keep on top of your responsibilities. You’ll use your cross-project exposure to feedback to the Data & Data Science Leadership Team to guide understanding, improve consistency, and develop & implement initiatives to improve the community for the future.

Who we’re looking for

You’ll need strong experience delivering and monitoring and scalable ML/AI solutions via automated ML Ops.

Ideally, you’ll also be technically skilled in most or all of the below:

- Expert knowledge of Python and SQL, inc. the following libraries: Numpy, Pandas, PySpark and Spark SQL

  • Expert knowledge of ML Ops frameworks in the following categories:
    a) experiment tracking and model metadata management (e.g. MLflow)
    b) orchestration of ML workflows (e.g. Metaflow)
    c) data and pipeline versioning (e.g. Data Version Control)
    d) model deployment, serving and monitoring (e.g. Kubeflow)

    - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform
  • Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn)
  • Working knowledge of object-oriented programming and unit testing in Python
  • Working knowledge of application and information security principles and practices (e.g. OWASP for Machine Learning)
  • Working knowledge of Unix-based CLI commands, source control and scripting
  • Working knowledge of containerisation (e.g. Docker) and container orchestration (e.g. Kubernetes)
  • Working knowledge of a cloud data platform (e.g. Databricks) and a data lakehouse architecture (e.g. Delta Lake)
  • Working knowledge of the AWS cloud technology stack (i.e. S3, Glue, DynamoDB, IAM, Lambdas, ELB, EKS)

    Rewards and benefits

    As you help us to shape the future, we’ve shaped our rewards and benefits to help you thrive and support your lifestyle:

    - Competitive salary
  • Discretionary group performance-based bonus
  • 25 days annual leave (plus Bank Holidays)
  • Single cover private medical insurance
  • Pension scheme

    We’re committed to making a tangible impact on the climate challenge we all face. Drax is where your individual purpose can work alongside your career drive. We work as part of a team that shares a passion for doing what’s right for the future. With Drax you can shape your career and a future for generations to come.

    Together, we make it happen.

    At Drax, we’re committed to fostering an environment where everyone feels valued and respected, regardless of their role. To make this a reality, we actively work to better represent the communities we operate in, foster inclusion, and establish fair processes. Through these actions, we build the trust needed for all colleagues at Drax to contribute their perspectives and talents, no matter their background. Find out more about our approach here.

    How to apply
    Think this role’s for
    you? Click the ‘apply now’ button to begin your Drax journey.
    If you want to find out
    more about Drax, check out our LinkedIn page to see our latest
    news.
    We understand that you
    may have some additional questions about the role. If you’d like to have a
    confidential chat to discuss the role in more detail, please email
    We
    reserve the right to close roles early when the particular role and / or
    location has had sufficient applications.

Related Jobs

View all jobs

Machine Learning Operations (ML Ops) Engineer

Machine Learning Operations Engineer - UK

Machine Learning Operations (ML Ops) Engineer...

Machine Learning Operations (ML Ops) Engineer

Machine Learning Consultant

Machine Learning Engineer

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for AI Jobs: 10 Tweaks That Triple Recruiter Views

In today’s fiercely competitive AI job market, simply having a LinkedIn profile isn’t enough. Recruiters and hiring managers routinely scout for top talent in machine learning, data science, natural language processing, computer vision and beyond—sometimes before roles are even posted. With hundreds of applicants vying for each role, you need a profile that’s optimised for search, speaks directly to AI-specific skills, and showcases measurable impact. By following this step-by-step LinkedIn for AI jobs checklist, you’ll make ten strategic tweaks that can triple recruiter views and position you as a leading AI professional. Whether you’re a fresh graduate aiming for your first AI position or a seasoned expert targeting a senior role, these actionable changes will ensure your profile stands out in feeds, search results and recruiter queues. Let’s dive in.

Part-Time Study Routes That Lead to AI Jobs: Evening Courses, Bootcamps & Online Masters

Artificial intelligence (AI) is reshaping industries at an unprecedented pace. From automating mundane tasks in finance to driving innovation in healthcare diagnostics, the demand for AI-skilled professionals is skyrocketing. In the United Kingdom alone, AI is forecast to deliver over £400 billion to the economy by 2030 and generate millions of new jobs across sectors. Yet, for many ambitious professionals, taking time away from work to upskill can feel like an impossible ask. Thankfully, part-time learning options have proliferated: evening courses, intensive bootcamps and flexible online master’s programmes empower you to learn AI while working. This comprehensive guide explores every route—from short tasters to deep-dive MScs—showcasing providers, course formats, funding options and practical tips. Whether you’re a career changer, a busy manager or a self-taught developer keen to go further, you’ll discover a pathway to fit your schedule, budget and goals.