Software Engineer - ML Enablement

As a Software Engineer within the Machine Learning Enablement Team at the BBC, you will design and deliver the tools, platforms, and capabilities that empower data scientists and engineering teams across the organisation. Your work will enable scalable, high-quality machine learning workflows and help shape the BBC’s future through innovative technology solutions.

You will work collaboratively with engineers, data scientists, and other technical teams to build reliable and maintainable software. You will have opportunities to develop your technical skills across software engineering, cloud, data, and machine learning technologies while contributing to solutions that have impact across the organisation., * Design, build and maintain tools, services, and infrastructure to support machine learning workflows.

• Apply strong engineering practices, including TDD, CI/CD, and clean software design principles.
• Contribute to architectural decisions and technical discussions.
• Contribute to data and machine learning pipelines and integrations.
• Engage with cross-functional teams to define requirements and deliver solutions.
• Conduct code reviews and contribute to testing, reliability, and security.
• Participate in pair programming and knowledge sharing to support team growth.

• Experience developing software using Python or a similar modern programming language.
• Good understanding of software engineering principles and practices, including testing, code quality, version control, and CI/CD.
• Experience developing or supporting cloud-based services, preferably using AWS.
• Experience with infrastructure-as-code and automated software delivery, such as AWS CDK, CloudFormation, or similar technologies.
• Experience developing or maintaining data, software, or machine learning-focused pipelines, with an understanding of monitoring, reliability, security, and operational support.

DESIRABLE

• Experience with AWS services such as SageMaker, S3, EC2, Lambda, IAM, VPC, KMS, or Bedrock.
• Experience developing or contributing to scalable architectures for data-driven products or services.
• Experience working with MLOps practices or machine learning workflows.
• Experience with containerisation and orchestration technologies.
• Familiarity with machine learning concepts, statistical techniques, or machine learning frameworks, and experience collaborating with data scientists or ML engineers.

.buttontext5e59931b164f1563 a{ border: 1px solid transparent; } .buttontext5e59931b164f1563 a: focus{ border: 1px dashed #1f619c !important; outline: none !important; } 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.

Before your start date, you may need to disclose any unspent convictions or police charges, in line with our Recruitment policy. This allows us to discuss any support you may need and assess any risks. Failure to disclose may result in the withdrawal of your offer.

Join a forward-thinking engineering community at one of the world’s most respected media organisations. The Machine Learning Enablement Team sits at the forefront of technical innovation, building state-of-the-art systems that directly support the BBC’s global impact. You’ll contribute to a modern engineering culture rooted in collaboration, continuous learning, and craftsmanship-while developing tools used across the organisation.

The BBC will support your growth with mentorship, learning opportunities, and exposure to modern cloud, data, and machine learning technologies. You’ll work alongside experienced engineers and have the opportunity to contribute to challenging technical problems while developing your skills and career.