Principal Software Engineer, Generative AI
Principal Software Engineer, Generative AI
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Job Description
Job Package
Job Reference: 24206
Band: D
Salary: 76700 - 87600 depending on relevant skills knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights.
Contract type: Permanent
Location: London Glasgow or Salford. This is a hybrid role and the successful candidate will balance office working with home working.
Were happy to discuss flexible working. Please indicate your choice under the flexible working question in the application. There is no obligation to raise this at the application stage but if you wish to do so you are welcome to. Flexible working will be part of the discussion at offer stage.
Excellent career progression the BBC offers great opportunities for employees to seek new challenges and work in different areas of the organisation.
Unrivalled training and development opportunities our in-house Academy hosts a wide range of internal and external courses and certification.
Benefits - We offer a negotiable salary package a flexible 35-hour working week for work-life balance and 25 days annual leave with the option to buy an extra 5 days a defined pension scheme and discounted dental health care and gym. You can find out more about working at the BBC by selecting this link to our candidate pack.
If you need to discuss adjustments or access requirements for the interview process please contact the . For any general queries please contact: .
Freelancers are eligible to apply for an internal role if they are on a Worker Contract and they have worked continuously for 6 months. If they have worked for less than 6 months continuously or have a break of 3 weeks or more between engagements they must seek Divisional HR approval to apply for an internal role prior to submitting an application.
Job Introduction
The BBC has been serving audiences online for more than 20 years. Across key products including BBC iPlayer News Sport Weather and Sounds we entertain educate and inform audiences in their millions every day.
But behind the scenes we have work to do. We are making the shift from being a broadcaster that speaks to our audiences to becoming a service that is directly shaped by them and designed around their wants and needs. AI is fundamental to this journey: enriching and expanding our content improving journalist workflows and powering personalised experiences for millions of audience members.
The new era of generative AI offers opportunities and challenges on a much larger scale. We are hiring software engineers across multiple seniority levels to join a cross-functional team that builds AI products for content production use cases focusing on generative AI. This team builds products end-to-end from innovative ideas to validated scalable production systems serving thousands of internal users and improving the experience of millions. We work with our Responsible AI team to keep public service values at the heart of these products ensuring they are aligned with our editorial values serve the public good and maintain audience trust.
We are a friendly and supportive team and we love that we get to work on interesting and important problems that have a real impact on the audiences experience and the future of the BBC. The BBC has an industry-leading engineering culture with a strong focus on best practice and a wide range of opportunities for learning and career growth. We strive for diverse representation of people and ways of thinking within the team and work in a friendly supportive and inclusive manner.
This team will build AI services that integrate with user-facing applications working closely with front-end engineering teams. Recent projects include:
- Fine-tuning and deploying open-source large language models on use cases that assist journalists and build audience engagement.
- Developing and deploying generative AI solutions to produce content metadata and improve the experience of hundreds of journalists and millions of users worldwide.
Main Responsibilities
- Writing clean maintainable well-tested production code in Python.
- Designing building iterating on and maintaining AWS infrastructure for AI deployments e.g. optimised LLM inference on GPUs reliable model training and fine-tuning pipelines CI/CD pipelines data stores model development environments interfaces with 3rd party models and scalable APIs.
- Working with data scientists to train and evaluate in-house ML models and systems based on 3rd party models build and validate prototypes then scale up into performant production systems.
- Following and iterating on our software engineering best practices such as code reviews pair programming TDD model/data versioning linting automated test coverage analysis infrastructure-as-code CI/CD and clear and comprehensive documentation.
- Responding to production issues and outages building monitoring infrastructure to ensure those instances are identified quickly and dealt with effectively and conducting PIRs and iterating on our infrastructure to ensure they dont happen again.
- Researching and experimenting with new AI technologies as they emerge.
- Mentoring more junior colleagues.
- Closely collaborating with other engineers and cross-functional teammates and stakeholders attending Agile ceremonies like stand-ups retros sprint planning and knowledge sharing sessions.
- Engaging with the wider engineering and ML community at the BBC.
Are you the right candidate
We are open to a range of backgrounds from ML engineers with hands-on model training and deployment experience to DevOps and MLOps engineers to strong general software engineers with a real desire to learn about AI.
You are encouraged to apply even if you dont meet every one of the criteria listed!
Essential criteria:
- Strong coding skills preferably in Python.
- Expertise in software engineering best practices such as testing code management and deployment.
- Experience designing and building cloud-based software ideally on AWS.
- Ability to clearly communicate to both technical and non-technical team members.
- Ability to work effectively in a cross functional team.
- Experience leading large and complex technical projects.
- Strong stakeholder engagement skills.
- Mentorship of more junior colleagues.
- A strong interest in AI.
Desirable experience:
- DevOps/MLOps experience e.g. deploying ML models setting up training pipelines model registries monitoring etc.
- Hands-on experience training and evaluating ML models.
- Managing databases and data pipelines.
- Experience with generative AI.
About the BBC
The BBC is committed to redeploying employees seeking suitable alternative employment within the BBC for different reasons 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.
We dont focus simply on what we do we also care how we do it. Our values and the way we behave are important to us. Please make sure youve read about our values and behaviourshere.
Diversity matters at the BBC. We have a working environment where we value and respect every individuals unique contribution enabling all of our employees to thrive and achieve their full potential.
We want to attract the broadest range of talented people to be part of the BBC whether thats to contribute to our programming or our wide range of non-production roles. The more diverse our workforce the better able we are to respond to and reflect our audiences in all their diversity.
We are committed to equality of opportunity and welcome applications from individuals regardless of age gender ethnicity disability sexual orientation gender identity socio-economic background religion and/or belief. We will consider flexible working requests for all roles unless operational requirements prevent otherwise.
To find out more about Diversity and Inclusion at the BBC please clickhere.
Required Experience:
Staff IC
Employment Type
Full-Time
