Senior MLOps Engineer - Hybrid, Source Focus

Fuzzy Labs is a fast-growing, Manchester-based tech consultancy that helps a diverse range of clients product ionise machine learning using Open Source MLOps. 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 prototyping new machine learning models to building scalable and secure production ML 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 experts, expand our role within the community, and continue to deliver high-quality solutions to our clients.

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.

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

• Loving what we do: a real passion for Open Source, MLOps, and taking pride in our work.
• Just trying it: MLOps is an exciting new field. 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.

Our engineers collaborate closely with their team leads and the customer to design and implement high quality solutions. We encourage our senior engineers to work with a high degree of autonomy and own work streams 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 leading demos and participating in workshops and training sessions.
• Designing and implementing features and full work streams to a high standard of engineering, including good documentation and automated testing.
• Contributing to sprint planning, retrospectives and code reviews, working with your team lead to design systems and plan their implementation.
• 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 MLOps community through R&D content.

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 machine learning research, or figuring out how to scale generative models in the cloud, 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, open source technologies, and setting the standards for their implementation and adoption.
• Strong experience building production-grade ML software in Python - this could include training and serving machine learning models, building large-scale inference services, or integrating .
• Experience deploying ML services in a cloud environment, for example AWS, Google Cloud or Azure, along with modern Dev Ops practices and infrastructure-as-code tooling.
• Fluency in our core tooling:
  Git,…