Applied AI Engineer

Fuzzy Labs; Manchester; On-site; GBP 90,000 - 120,000; Full time

Benefits offered by this job

25 days holiday rising to 30

Enhanced family leave

£500 annual development budget

Equity option scheme

Hybrid working in central Manchester

Cycle to Work Scheme

Volunteer time off

Company socials

Job summary

Fuzzy Labs, a Manchester-based tech consultancy, seeks engineers to design, build and productionise AI systems with open source tech. You’ll work across AI lifecycle, from prototyping to secure production deployments, collaborating with clients and internal teams.

You will apply strong software engineering, applied AI, and problem-solving skills to deliver reliable, scalable solutions while staying at the forefront of AI tooling and MLOps. Hybrid work in Manchester is offered.

Qualifications

• An undergraduate degree in computer science, mathematics, or similar, or a relevant postgraduate degree.
• A passion for coding, machine learning, AI, and open source technologies.
• Proven experience building production-grade software in Python, incl. training models, serving models, or APIs.
• Experience with ML or generative AI systems, such as LLM-powered applications, RAG pipelines, embeddings, or model serving.
• Experience with cloud computing (AWS, Google Cloud, Azure) and modern DevOps practices.
• Fluency in Git, Unix/Linux, Docker; strong IDE/editor preference welcome.
• Awareness of the AI landscape and willingness to deepen knowledge.

Responsibilities

• Collaborate with teams to design and implement AI solutions.
• Build production-grade AI systems and secure, reliable services.
• Develop features with good documentation, testing, observability, and maintainable code.
• Work on modern AI tooling including LLM apps, retrieval-augmented generation, model serving.
• Participate in sprint planning, reviews, and planning with team lead.
• Stay up-to-date with fast-moving industry and share learnings.

Skills

Python production-grade

ML/AI systems

Cloud computing basics

Open source technologies

MLOps

Git & Unix/Linux

Problem solving

Education

Bachelor's degree in CS/Math or related

Tools

Git

Unix/Linux

Docker

Job description

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 engineers looking for a forward-deployed engineering role where they can combine strong software engineering, applied AI, 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 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 engineers to work with a high degree of autonomy and take part in 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, participating in discovery workshops, visiting customer sites where useful, presenting back our solutions in demos, and supporting training sessions.
• Designing, building and deploying production‑grade AI systems, from early prototypes through to secure, reliable services that users can depend on.
• Implementing features to a high standard of engineering, including good documentation, automated testing, observability and maintainable code.
• 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.
• Contributing to sprint planning sessions, retrospectives and code reviews, working with your team lead to plan your project work.
• 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, and open source technologies.
• Proven experience building production‑grade software in Python. This could include training models from scratch, serving models as web 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 with cloud computing, for example AWS, Google Cloud or Azure, along with modern DevOps practices and infrastructure‑as‑code tools.
• Fluency in our core tooling: Git, Unix/Linux, Docker, and common open‑source AI, ML or MLOps tools. Plus, a strong opinion on your IDE / editor of choice is welcome ;)
• 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 you’ll learn as you go by immersing yourself in this fast‑moving field.

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
• £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.