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Salary: Up to £50,000 p/a (depending on skills and experience) plus staff share of profit and excellent benefits.
Job type: Permanent and Full Time (35 hours p/w)
Reporting to: Head of Engineering
Location: Edinburgh, Scotland - Hybrid working
We support people to work from wherever they are most comfortable, but we understand the importance of coming together to collaborate, socialise and build relationships, so our jobs are all part of a hybrid working approach.
ABOUT GOOD-LOOP
Good-Loop makes it easy and profitable for big brands to do good at scale. Our mission is to create a positive role for advertising in society and we do that by building products that help brands plan, measure and buy Good-Media. They’re ads, except they’re good.
We work with the biggest brands in the world, from Nike and Adidas to L’Oreal, Doritos, Nature Valley and Toyota to deliver attention-earning, sustainable ads that prove doing good is good for business. And our carbon-neutral advertising has raised over $11m for good causes around the world – all while supporting quality journalism and diverse publications.
As the first carbon neutral B Corp in AdTech, Good-Loop is uniquely positioned to capitalise on the increasing consumer demand for businesses to step up and contribute to society. We’re a small, but agile and fast-moving team with a lot of heart and even more ambition.
ABOUT THE ROLE
As a Data Engineer with AI Experience, you will play a key role in designing, developing, and optimising scalable data pipelines and infrastructure. You will collaborate with data scientists, AI engineers, and cross-functional teams to integrate AI models into production environments while ensuring data integrity, security, and efficiency.
Responsibilities:
- Design, implement, and maintain scalable data pipelines and infrastructure.
- Develop data ingestion processes from various sources, ensuring reliability and efficiency.
- Collaborate with cross-functional teams to understand data and AI model requirements and deliver robust solutions.
- Optimise data pipelines for performance, reliability, and scalability.
- Ensure data quality and integrity through validation and monitoring processes.
- Implement data security and privacy measures to protect sensitive information.
- Build and deploy machine learning pipelines and support AI-driven applications.
- Collaborate with data scientists and AI engineers to ensure seamless integration of AI models into production environments.
- Stay updated with emerging technologies and best practices in data engineering and AI.
Experience:
- Experience in designing and building data pipelines and infrastructure.
- Proficiency in programming languages such as Python, Java, or Scala.
- Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
- Strong understanding of database technologies, SQL, and NoSQL databases.
- Experience working with AI frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn.
- Familiarity with building and deploying machine learning models in production environments.
- Excellent problem-solving skills and ability to troubleshoot complex data and AI-related issues.
- Strong communication and collaboration skills.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- Knowledge of MLOps practices, including model monitoring and versioning.
Key Performance Indicators (KPIs):
- Timely delivery of scalable data and AI-driven solutions.
- Data pipeline performance and reliability metrics.
- Data quality metrics and resolution of data issues.
- Implementation of data security and privacy measures.
- Successful deployment and performance of AI models in production.
- Efficiency and scalability of AI model inference pipelines.
- Contribution to team knowledge and adoption of best practices.
Research shows that while men apply for jobs when they meet an average of 60% of the criteria, women and other marginalised groups tend to only apply when they tick every box. So if you think you have what it takes, but don’t necessarily meet every single requirement on the list above, please still get in touch. We’d love to have a chat and hear about what else you know.
WHY JOIN US?
We care about leaving the world a little bit better than we found it, we’re a passionate and kind team and we’re constantly asking what else we can do to push our industry, and our work, to be better.
We pride ourselves on a relaxed but productive working environment enabling both commercial success and personal development. No matter what stage of your career you're at - from paid internships and graduate opportunities right through to senior posts - we'll support you with the training and development you need to feel empowered to do your best work.
We strive to make Good-Loop a place where everyone can do their best work, by bringing together diversity of thought, perspectives, and experience, to create an inclusive environment where our people can be their best selves.
We welcome differences whether it’s gender, gender identity or expression, race, disability, age, sexual orientation, religion or belief, marital status, national origin, veteran status, or pregnancy and maternity status; so please, just be yourself.
HOW DO I APPLY?
If you’re applying for a tech role, we’d love to see a short portfolio of your best work. This could be a link to your github profile with a paragraph of commentary, or you could send some code samples. Show us projects you are passionate about, regardless of whether they are relevant to this job. Hobby projects preferred!
If you need us to make reasonable adjustments to ensure that your interview experience is a great one, please feel free to let us know by emailing
For more information on us, please visit our website and follow Good-Loop on our social channels via Instagram, LinkedIn, Twitter and YouTube.
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