Senior MLOps/GenAI Infrastructure Engineer

BBC Group and Public Services; London, Salford, Newcastle upon Tyne, Glasgow, Cardiff; Hybrid; GBP 59,000 - 70,000; Full time

Job summary

Join BBC as a Senior MLOps/GenAI Infrastructure Engineer and play a pivotal role in shaping the future of media through cutting-edge ML and AI technologies. You'll craft innovative tools that empower teams across the organization while enjoying competitive pay and flexible working arrangements.

Benefits

Flexible working hours

25 days annual leave plus the option to buy 5 additional days

Defined pension scheme

Discounted dental and health care

Qualifications

• Extensive experience building and delivering scalable infrastructure for ML applications.
• Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation.
• Strong understanding of machine learning lifecycle and serving models in production.

Responsibilities

• Designing, developing, and maintaining tools for MLOps workflows.
• Collaborate with Data Scientists to deploy and monitor models.
• Implement Infrastructure-as-Code with AWS services.

Skills

DevOps/MLOps experience

Designing and maintaining tools

Collaboration with Data Scientists

Debugging and troubleshooting skills

Building CI/CD pipelines

Education

Bachelor's or Master's degree in Computer Science or Engineering

Tools

AWS (SageMaker, Bedrock, etc.)

Docker

Kubernetes

Git/GitHub

CI/CD tools (e.g., GitHub Actions)

Job description

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• Job Title: Senior MLOps/GenAI Infrastructure Engineer
• Location: London / Salford / Glasgow / Newcastle / Cardiff (This is a hybrid role and the successful candidate will balance office working with home working)
• Band: D
• Salary: up to £59,600 - £69,800 (The expected salary range for this role reflects internal benchmarking and external market insights.)

We’re happy to discuss flexible working. Please indicate your preference under the flexible working question in the application. There’s no obligation to raise this at the application stage, but if you wish to do so, you’re welcome to. Flexible working will be part of the discussion at offer stage.

Purpose Of The Role

Step into the world of the BBC, one of the UK's most iconic and beloved brands, where every working day is as unique as it is rewarding. Every tick of the clock, our content reaches millions of people globally, which is made possible by our top-notch Software Engineering team. They've been instrumental in pioneering innovative products and unique features that have firmly positioned us at the forefront of our industry. We don't merely adapt to an ever-changing world - we set the pace.

With this role you'll be at the heart of an exciting journey, crafting tools and patterns that are state-of-the-art and transformative. We are the catalysts, enabling the creation and collaboration of cutting-edge ML and AI technologies. Our work is pivotal in shaping the BBC's future, empowering teams across the organisation to explore, innovate, and redefine the landscape of media. Our team is building out new tools and capabilities to accelerate data science activities and the development of ML/GenAI applications. We enable teams across the BBC to build, collaborate on, manage, and maintain their machine learning platforms at scale.

You will play a key role in driving our ambition to build an outstanding software engineering team, environment, and culture. We are looking for a Senior Engineer to join our tech community to drive this transformation, build a modern digital ecosystem using exciting technologies and do the best work of their careers.

Your Key Responsibilities And Impact

• Designing, developing, and maintaining tools that support data science and MLOps/LLMOps workflows.
• Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock
• Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments.
• Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline, CodeBuild, Jenkins.
• Integrate monitoring and observability tools such as AWS CloudWatch, Prometheus, Grafana for infrastructure and model health tracking.
• Ensure software quality through Test-Driven Development (TDD), unit testing frameworks (e.g., pytest, unittest), and automated integration tests.
• Conduct regular code reviews, participate in pair programming, and advocate for clean code, modular design, and maintainable architecture.
• Collaborate with architects and stakeholders to design high-level system architecture for cloud-first, AI-integrated products.
• Enforce security best practices (IAM, encryption, VPC configuration, audit logging) using AWS native services and third-party tools.
• Embed security throughout the software development lifecycle by integrating static and dynamic code analysis, vulnerability scanning, and policy-as-code tools into CI/CD pipelines—ensuring DevSecOps principles are applied from design to deployment.
• Promote a culture of continuous learning and knowledge-sharing through comprehensive documentation, technical deep dives, brown bag sessions, internal workshops, and active mentorship of team members.

Your Skills And Experience

• Extensive experience of DevOps/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies
• Experience with cloud services, especially Amazon Web Services (AWS) – SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS.
• Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation.
• Experience implementing and scaling MLOps workflows with tools such as MLflow, SageMaker Pipelines.
• Proven experience building, containerising, and deploying using Docker and Kubernetes.
• Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub.
• Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation.
• Familiarity with security and compliance practices for cloud-hosted applications.
• Excellent debugging, troubleshooting, and optimisation skills across the stack.
• Solid understanding of machine learning lifecycle and serving LLMs in production environments.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Certifications such as AWS Certified DevOps Engineer, AWS ML Engineer, AWS Certified Solutions Architect,
• Strong communication skills, with experience working in Agile teams (Scrum, Kanban) and cross-functional collaboration.
• Contributions to open-source GenAI, MLOps, or LLMOps projects or communities is a strong plus.

Disclaimer

This job description is a written statement of the essential characteristics of the job, with its principal accountabilities, incorporating a note of the skills, knowledge and experience required for a satisfactory level of performance. This is not intended to be a complete, detailed account of all aspects of the duties involved.

Please note: If you were to be offered this role, the BBC will conduct Employment screening checks which include Reference checks; Eligibility to work checks; and if applicable to the role, Safeguarding and Adverse media/Social media checks. Any offer made is conditional on these checks being satisfactory.

The BBC is committed to redeploying employees seeking suitable alternative employment within the BBC and they will be given priority consideration ahead of other applicants. Priority consideration means for those employees seeking redeployment their application will be considered alongside anyone else at risk of redundancy, prior to any individuals being considered who are not at risk.

Information at a Glance

This is your BBC

At the BBC you can create and innovate in an inclusive environment while contributing to some of the world’s best loved content, and the BBC’s mission to inform, educate and entertain.

Find out more about the BBC

Life at BBC

Here you will benefit from:

• Fair pay and flexible benefits including a competitive salary package, a flexible 35-hour working week, 25 days annual leave with the option to buy an extra 5 days, a defined pensionscheme and discounted dental, health care and gym.
• Excellent career and professional development.
• Support in your working life, including flexible working which you can discuss with us at any point during the application, selection or offer.
• A values-based organisation where the way we do things is important as what we do.

Benefits may vary if you are joining on an FTC basis.

Learn more about life at the BBC and our values in our candidate pack.

Candidate pack

You belong

We have a working environment where we value and respect every individual's unique contribution, so all our employees feel that they can belong, thrive and achieve their full potential.

We want to attract the broadest range of talented people to join us. The more diverse our workforce, the better able we are to respond to and reflect our audiences in all their diversity.

We welcome applications from individuals, regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion and/or belief.

Find out more about diversity, inclusion and belonging in our strategy below.

Diversity, inclusion & belonging strategy

Disability confident

We are a disability confident employer. If you need to discuss adjustments or access requirements for the interview process, or to carry out this role, please contact us via email and we’d be happy to discuss: [e-mail]

BBC Group and Public Services, Broadcasting House, Portland Place, London, United Kingdom, W1A 1AA. BBC Studios Distribution Limited, company no: 01420028, registered address: 1 Television Centre, 101 Wood Lane, London, United Kingdom W12 7FA.