Senior Applied AI Engineer

About us

Fuzzy Labs is a fast-growing, Manchester-based tech consultancy that helps a diverse range of clients build, deploy, and productionise AI systems using open source technologies. We exist to help our customers harness and channel the power of AI safely and effectively, to make positive change and use AI for good.

Our work sits across the whole development lifecycle, from exploring and prototyping new AI use cases to building scalable, secure, production-grade machine learning and generative AI systems, and everything in between. Our work spans disruptive startups, multi-national organisations, policing, and secure government sectors, providing you with the unique opportunity to make a tangible, real-world impact.

We’ve had considerable growth over the last few years and we’re looking to continue with this momentum as we build on our reputation as Open Source MLOps and applied AI experts, expand our role within the community, and continue to deliver high-quality solutions to our clients.

What we’re looking for

The ideal candidate will be motivated to grow and progress in line with the company’s ambitions: we’re looking for passionate engineers with an appetite for keeping up with the cutting edge, an eye for detail, and a knack for creative problem solving.

This role suits experienced engineers looking for a forward-deployed engineering role where they can combine strong software engineering, applied AI, technical leadership, and hands-on customer problem solving. You’ll work close to the people using what we build, helping turn ambiguous AI opportunities into reliable production systems.

As a Senior Applied AI Engineer, we’ll look to you to take ownership of complex technical workstreams, help shape the direction of projects, support other engineers, and work confidently with customers to understand their needs and deliver high-quality solutions.

As well as being a great engineer, motivated by the chance to be at the forefront of applied AI, you’ll also enjoy being part of a culture that values:

• Loving what we do: a real passion for open source, applied AI, MLOps, and taking pride in our work.
• Just trying it: AI is moving quickly. We love to develop new skills, solve new problems and thrive on a challenge.
• Being greater than the sum of parts: we are a team, one that isn’t just us but our customers and our community.
• Positive impact: AI is going to change the world. We choose to use it for good and leave a positive legacy.

A typical day

Our engineers collaborate closely with their team leads and the customer to design and implement high quality AI solutions. We encourage our senior engineers to work with a high degree of autonomy and own workstreams across every stage of the project delivery lifecycle, including:

• Working closely with clients to understand their needs, build strong relationships, and bring them along on the journey. This includes helping shape ambiguous problems, leading demos, participating in discovery workshops, visiting customer sites where useful, and supporting training sessions.
• Taking ownership of technical workstreams, from early discovery and prototyping through to the design, build and deployment of secure, reliable, production-grade AI systems.
• Designing and implementing features and full workstreams to a high standard of engineering, including good documentation, automated testing, observability, maintainable code and clear technical decision-making.
• Building with modern AI techniques and tooling, which may include LLM-powered applications, retrieval augmented generation, model serving, evaluation frameworks, AI agents, data pipelines, and cloud-native infrastructure.
• Working with your team lead and other engineers to design systems, plan implementation, break down technical work, and manage delivery risks.
• Contributing to sprint planning, retrospectives and code reviews, while helping maintain high engineering standards across the team.
• Supporting and mentoring other engineers by sharing context, reviewing technical approaches, and helping the team make good engineering decisions.
• Ensuring our high engineering standards are maintained and our clients are delighted.
• Staying up-to-date with a fast-moving industry, embracing new tools and frameworks, and sharing our learnings with the team.

As well as client work, we also set aside time to work on R&D projects and produce content in the form of blogs and videos. These projects are how we keep on top of a fast-moving technology landscape, in addition to being our greatest source of marketing. You’ll have the opportunity to craft your own voice in the applied AI and MLOps community through R&D content.

Skills and Experience

Our team is made up of a mix of backgrounds. We are looking for smart, curious people who are always expanding their knowledge and exploring new and emerging technologies. If you get excited about keeping up with the newest AI tools, figuring out how to scale generative AI systems in the cloud, or turning prototypes into production software, then you’ll fit right in. Some of the skills and experience we look for include:

• An undergraduate degree in computer science, mathematics, or similar, or a relevant postgraduate degree.
• A passion for coding, machine learning, AI, open source technologies, and setting high standards for their implementation and adoption.
• Strong experience building production-grade software in Python. This could include training and serving machine learning models, building large-scale inference services, integrating data stores, building APIs, or deploying AI-powered applications.
• Experience with machine learning or generative AI systems, such as LLM-powered applications, RAG pipelines, embeddings, prompt engineering, model evaluation, agents, model serving, or ML workflows.
• Experience designing and delivering cloud-based systems, for example using AWS, Google Cloud or Azure, along with modern DevOps practices and infrastructure-as-code tooling.
• Experience making technical decisions across a project or workstream, including balancing delivery speed, reliability, security, maintainability and customer needs.
• Experience delivering software using an agile development methodology.
• Fluency in our core tooling: Git, Unix/Linux, Docker, and common open-source AI, ML or MLOps tools.
• You should be aware of the broad landscape of AI and machine learning applications, tools, and technologies and willing to deepen your knowledge.

We encourage you to apply even if you don’t meet all of the requirements. Applied AI is an emerging field, sitting at the intersection of software engineering, machine learning engineering, data science, DevOps and product delivery. We’re excited to speak to candidates from any of these backgrounds; you don’t need an explicit MLOps or applied AI job title already, as long as you have strong engineering foundations and are excited to immerse yourself in this fast-moving field.

Benefits

By joining a growing company you’ll have the chance to make a real impact on its future. There’s plenty of room for growth and we’ll work with you to help you realise your technical and personal ambitions because your success and the company’s success are one and the same.

• 25 days holiday rising to 30 with each year of service
• Enhanced family leave, including maternity, paternity and adoption leave
• Healthcare cash plan
• £500 annual personal development budget and AI assistant of your choice
• Equity option scheme, giving you a genuine stake in the business
• Hybrid working in a vibrant, central Manchester office with free fruit, cereals, and hot & cold drinks
• Cycle to Work Scheme and secure bike storage
• Paid time off for charity and volunteering
• Company socials, summer and Christmas parties

Location and Eligibility

As a hybrid-working organisation, we bring the team together in the office three days each week on Mondays, Wednesdays and Thursdays, and work remotely on the remaining days. We have found that regular, structured time in person enables us to make decisions more quickly, collaborate more effectively, and build the strong working relationships that underpin our work.

For that reason, being able to join us in our central Manchester office on those set days is an essential part of the role. At the same time, we recognise that personal circumstances vary. We aim to approach individual situations with flexibility and openness, and we’re always willing to have a conversation where specific needs arise.

Some client work may also involve occasional travel to customer sites across the UK. We see this as an important part of Applied AI: getting close to the people, systems and environments we’re building for. Travel will vary by project and will be planned with reasonable notice.

Finally, due to the sensitive nature of some projects, you will be required to undergo UK government security clearance after you start, at SC level. This will include a credit check and criminal records check. As a result, we’re only able to consider candidates who have been resident in the UK for 5 or more years.

Interested?

If you’d like to work with us, please use the link below.

Please include a few words about yourself and what interests you about the role, and a link to your GitHub, Bitbucket or similar. If you’re on Kaggle, have a tech blog, a cool side-project, or an Instagram for your cat, dog, etc, send us that too!

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