About Us

We’re a visionary startup dedicated to reshaping the boundaries of what’s possible with AI. While we may be small, our ambitions are anything but. We believe that diverse perspectives and thoughtful experimentation drive innovation, and we’re committed to creating breakthroughs by approaching problems from fresh, unconventional angles. Join us to be part of something transformative.

The Role

Design machine learning solutions that excel in the complex realities of live production. As our Senior Machine Learning Engineer, you’ll play a pivotal role in the end-to-end lifecycle of ML models: from data exploration and development to deployment, monitoring, and continuous improvement. We’re seeking someone with a proven track record of transforming prototypes into production-grade implementations that deliver real-world impact.

The Office

We’re based in the city centre of Manchester and work collaboratively in the office 3 days a week, Tuesday to Thursday, every week, with the occasional in-person meeting on a Monday or Friday. We like collaboration, making decisions quickly, and offering a workspace environment where people can share ideas and have direct input into everything we do.

MLOps Focus

Take ownership of the practices that ensure our machine learning models operate seamlessly in production. This includes building and maintaining automated testing frameworks, optimising deployment processes, and implementing robust version control systems tailored for ML workflows. You have a proven track record of successfully deploying models, moving beyond prototypes to create scalable, reliable production systems.

Collaboration and Leadership

You’ll guide data scientists, data engineers, and other stakeholders. You’ll also give thoughtful feedback to up-and-coming teammates, ensuring everyone’s efforts align with business objectives.

Adaptive Mindset

We value a flexible approach to balancing ambitions with practical constraints. You’ll need to work closely with teams across the business, listening to different viewpoints and deciding how best to introduce ideas in ways that make sense for each situation.

Key Responsibilities

• Design and maintain scalable data pipelines for data cleaning, analysis, and modeling.
• Develop, test, and deploy machine learning models, ensuring scalability and reliability in production environments.
• Monitor and evaluate model performance, implementing swift improvements to address data drift and changing requirements.
• Mentor and coach junior team members, fostering their growth and adherence to best practices.
• Collaborate cross-functionally, sharing insights to influence strategic decisions and business outcomes.
• Champion a culture of curiosity and critical thinking, promoting open discussions on ethics, transparency, and data privacy.

What We’re Looking For

• Proven experience delivering machine learning models from prototyping to live deployment at scale.
• Expertise with MLOps tools and practices (e.g., Docker, CI/CD pipelines, monitoring frameworks).
• Strong proficiency in Python and libraries like Pandas, NumPy, and scikit-learn, with familiarity in frameworks like TensorFlow or PyTorch being a plus.
• Experience with cloud platforms such as AWS, Azure, or GCP, including deploying and managing models in cloud environments.
• Solid understanding of data governance, security, and compliance in production settings.
• Exceptional communication skills, with an ability to explain complex technical concepts to non-technical audiences.
• A proactive mindset, ready to challenge assumptions and inspire constructive dialogue across the team.

Why Join Us

You’ll gain the chance to influence projects that push the boundaries of machine learning and AI, all while shaping a culture that welcomes new perspectives. We believe in nurturing talent through shared learning, open dialogue, and continuous iteration. If you’re motivated by creating a truly greenfield technology and making it happen, we’d love to hear from you.