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<h3>MLOps Fellow</h3>
<p><strong>About us</strong></p>
<p>Fuzzy Labs is a fast-growing, Manchester-based tech consultancy that helps a diverse range of clients productionise 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.</p>
<div>MLOps is the discipline of reliably deploying, monitoring, and maintaining machine learning models in the real world, bridging the gap between data science and production engineering. This is a skillset of increasing importance as AI becomes more ubiquitous, and is Fuzzy Labs’ core strength.</div>
<div>&nbsp;</div>
<div>As we grow our team, we're launching our Fellowship Programme to bring in the next generation of MLOps engineers. This is a structured, hands-on programme designed to take talented people with strong foundations and turn them into well-rounded MLOps practitioners.&nbsp;</div>
<div>&nbsp;</div>
<div>
<div><strong>About the fellowship</strong></div>
<div>The fellowship is a paid, 9-month fixed-term programme with a clear pathway to a permanent role for those who thrive. You will be matched with a mentor, work on real client projects, and follow a structured curriculum covering everything from ML fundamentals to DevOps to model serving.</div>
<div>&nbsp;</div>
<div>The programme runs in three phases:</div>
<ul>
<li><strong>Getting started.</strong> The first week or so is an intensive supervised mini-project, designed to get you up to speed with our tooling and ways of working, and to help us understand your current strengths and weaknesses.</li>
<li><strong>Building core skills. </strong>You will rotate across client projects as a supported member of the team, building skills across machine learning engineering, DevOps, and AI tooling through a mix of pairing with your mentor and taking on tickets independently.</li>
<li><strong>Specialising and stepping up. </strong>In the later months you will focus on either model training or model serving, take on greater responsibility, and begin contributing as a junior engineer in your own right, with a personal development plan to guide your growth.</li>
</ul>
<div>By the end of the programme, the goal is simple: you are ready to work as a mid-level MLOps engineer.</div>
<div>&nbsp;</div>
<div>
<div><strong>What we're looking for</strong></div>
<div>The ideal fellow is someone who has recently completed (or is about to complete) a Master's degree or PhD in a STEM field, and is looking for a way into the world of production AI and MLOps. We'll also consider strong final-year undergraduates and early-career professionals coming from adjacent fields. What matters most is ability and enthusiasm.</div>
<div>&nbsp;</div>
<div><strong>You'll be a great fit if you value:</strong></div>
<div><strong>Loving what we do:</strong> a real passion for AI, open source, and building things that work in the real world.<br><strong>Just trying it:</strong> MLOps is a fast-moving space. We want people who are excited to learn, not intimidated by what they don't yet know.<br><strong>Being greater than the sum of parts:</strong> you'll be joining a team, and we care about collaboration as much as individual output.<br><strong>Positive impact: </strong>AI is going to change the world. We choose to use it for good.</div>
<div>&nbsp;</div>
<div><strong>A typical day</strong></div>
<div>Fellows work alongside our engineering teams on client projects from early in the programme. You won't be doing busywork, you’ll be getting real experience. After a short onboarding period, you'll be taking on real tickets, pairing with experienced engineers, and building things that matter to clients. As the programme progresses, you'll take on more responsibility and operate with greater independence.</div>
<div>&nbsp;</div>
</div>
<div>
<div><strong>Skills and experience</strong></div>
<div>We're looking for people who are curious, driven, and ready to grow.&nbsp;</div>
<div>&nbsp;</div>
<div>Essential:</div>
<ul>
<li>Recently completed or near-completing a Master's or PhD in a STEM subject (strong undergraduates also considered)</li>
<li>Confident coding in Python. Not necessarily production-grade, but demonstrably strong</li>
<li>Familiarity with Git and working collaboratively on code</li>
<li>A genuine interest in AI, machine learning, and how they're applied in real systems</li>
</ul>
</div>
</div>
<div>Strong indicators you'll stand out:</div>
<div>
<ul>
<li>Personal projects with a meaningful ML component</li>
<li>Experience with experiment tracking, data versioning, or similar MLOps-adjacent tooling</li>
<li>Automated testing experience (unit tests, integration tests, etc.)</li>
<li>Active participation in the tech community — attending events, writing, contributing to open source</li>
</ul>
<div>
<div>Benefits</div>
<div>
<ul>
<li>25 days holiday, pro rata</li>
<li>Health care cash plan</li>
<li>Enhanced family leave, including maternity, paternity and adoption leave</li>
<li>Hybrid working in a vibrant, central Manchester office with free fruit, cereals, and hot &amp; cold drinks</li>
<li>Paid time off for charity and volunteering</li>
<li>Cycle to Work Scheme and secure bike storage</li>
<li>Company socials, summer and Christmas parties</li>
<li>A clear pathway to a permanent role at the end of the programme</li>
</ul>
<div>&nbsp;</div>
<div>
<div><strong>Location and Eligibility</strong><br>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.&nbsp;For that reason, being able to join us in our central Manchester office on those set days is an essential part of the role.&nbsp;</div>
<div>&nbsp;</div>
<div>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.</div>
<div>&nbsp;</div>
<div>Finally, due to the sensitive nature of some projects, you may be required to undergo UK government security clearance at SC level. This would 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.</div>
<div>&nbsp;</div>
<div><strong>Interested?</strong><br>If you’d like to work with us, please apply here.&nbsp;Please include a few words about yourself and what interests you in Fuzzy Labs and the fellowship, and add a link to your Github (or Bitbucket, etc). If you’re on Kaggle, or have a tech blog, cool side-project, or an Instagram for your cat, dog, etc, send us that too!</div>
<div>&nbsp;</div>
</div>
</div>
</div>
</div>
</div></body></html>

<div>
<h3>MLOps Fellow</h3>
<p><strong>About us</strong></p>
<p>Fuzzy Labs is a fast-growing, Manchester-based tech consultancy that helps a diverse range of clients productionise 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.</p>
<div>MLOps is the discipline of reliably deploying, monitoring, and maintaining machine learning models in the real world, bridging the gap between data science and production engineering. This is a skillset of increasing importance as AI becomes more ubiquitous, and is Fuzzy Labs’ core strength.</div>
<div> </div>
<div>As we grow our team, we're launching our Fellowship Programme to bring in the next generation of MLOps engineers. This is a structured, hands-on programme designed to take talented people with strong foundations and turn them into well-rounded MLOps practitioners. </div>
<div> </div>
<div>
<div><strong>About the fellowship</strong></div>
<div>The fellowship is a paid, 9-month fixed-term programme with a clear pathway to a permanent role for those who thrive. You will be matched with a mentor, work on real client projects, and follow a structured curriculum covering everything from ML fundamentals to DevOps to model serving.</div>
<div> </div>
<div>The programme runs in three phases:</div>
<ul>
<li>
<strong>Getting started.</strong> The first week or so is an intensive supervised mini-project, designed to get you up to speed with our tooling and ways of working, and to help us understand your current strengths and weaknesses.</li>
<li>
<strong>Building core skills. </strong>You will rotate across client projects as a supported member of the team, building skills across machine learning engineering, DevOps, and AI tooling through a mix of pairing with your mentor and taking on tickets independently.</li>
<li>
<strong>Specialising and stepping up. </strong>In the later months you will focus on either model training or model serving, take on greater responsibility, and begin contributing as a junior engineer in your own right, with a personal development plan to guide your growth.</li>
</ul>
<div>By the end of the programme, the goal is simple: you are ready to work as a mid-level MLOps engineer.</div>
<div> </div>
<div>
<div><strong>What we're looking for</strong></div>
<div>The ideal fellow is someone who has recently completed (or is about to complete) a Master's degree or PhD in a STEM field, and is looking for a way into the world of production AI and MLOps. We'll also consider strong final-year undergraduates and early-career professionals coming from adjacent fields. What matters most is ability and enthusiasm.</div>
<div> </div>
<div><strong>You'll be a great fit if you value:</strong></div>
<div>
<strong>Loving what we do:</strong> a real passion for AI, open source, and building things that work in the real world.<br><strong>Just trying it:</strong> MLOps is a fast-moving space. We want people who are excited to learn, not intimidated by what they don't yet know.<br><strong>Being greater than the sum of parts:</strong> you'll be joining a team, and we care about collaboration as much as individual output.<br><strong>Positive impact: </strong>AI is going to change the world. We choose to use it for good.</div>
<div> </div>
<div><strong>A typical day</strong></div>
<div>Fellows work alongside our engineering teams on client projects from early in the programme. You won't be doing busywork, you’ll be getting real experience. After a short onboarding period, you'll be taking on real tickets, pairing with experienced engineers, and building things that matter to clients. As the programme progresses, you'll take on more responsibility and operate with greater independence.</div>
<div> </div>
</div>
<div>
<div><strong>Skills and experience</strong></div>
<div>We're looking for people who are curious, driven, and ready to grow. </div>
<div> </div>
<div>Essential:</div>
<ul>
<li>Recently completed or near-completing a Master's or PhD in a STEM subject (strong undergraduates also considered)</li>
<li>Confident coding in Python. Not necessarily production-grade, but demonstrably strong</li>
<li>Familiarity with Git and working collaboratively on code</li>
<li>A genuine interest in AI, machine learning, and how they're applied in real systems</li>
</ul>
</div>
</div>
<div>Strong indicators you'll stand out:</div>
<div>
<ul>
<li>Personal projects with a meaningful ML component</li>
<li>Experience with experiment tracking, data versioning, or similar MLOps-adjacent tooling</li>
<li>Automated testing experience (unit tests, integration tests, etc.)</li>
<li>Active participation in the tech community — attending events, writing, contributing to open source</li>
</ul>
<div>
<div>Benefits</div>
<div>
<ul>
<li>25 days holiday, pro rata</li>
<li>Health care cash plan</li>
<li>Enhanced family leave, including maternity, paternity and adoption leave</li>
<li>Hybrid working in a vibrant, central Manchester office with free fruit, cereals, and hot &amp; cold drinks</li>
<li>Paid time off for charity and volunteering</li>
<li>Cycle to Work Scheme and secure bike storage</li>
<li>Company socials, summer and Christmas parties</li>
<li>A clear pathway to a permanent role at the end of the programme</li>
</ul>
<div> </div>
<div>
<div>
<strong>Location and Eligibility</strong><br>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. </div>
<div> </div>
<div>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.</div>
<div> </div>
<div>Finally, due to the sensitive nature of some projects, you may be required to undergo UK government security clearance at SC level. This would 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.</div>
<div> </div>
<div>
<strong>Interested?</strong><br>If you’d like to work with us, please apply here. Please include a few words about yourself and what interests you in Fuzzy Labs and the fellowship, and add a link to your Github (or Bitbucket, etc). If you’re on Kaggle, or have a tech blog, cool side-project, or an Instagram for your cat, dog, etc, send us that too!</div>
<div> </div>
</div>
</div>
</div>
</div>
</div>

Fuzzy Labs

MLOps Fellow

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