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Monzo is a fintech company on a mission to transform banking and make money work for everyone. The Machine Learning Operations team is building state-of-the-art systems to revolutionize customer service by reducing resolution time and effort while enhancing satisfaction.
In this role, you'll serve as a technical individual contributor providing leadership in developing ML-based solutions for customer operations. You'll leverage advanced techniques including large language models (LLMs), retrieval-augmented generation (RAG), and autonomous agents to understand customer problems and build human-in-the-loop systems that augment automation with support staff efforts. This enables efficient prediction, identification, disambiguation, and routing of customer issues at scale across multiple geographies.
Your day-to-day responsibilities include:
- Collaborating with stakeholders across the organization to identify high-impact opportunities to transform Customer Operations with machine learning
- Leading the design and development of advanced ML models, exploring LLMs, RAG, and sequence-based architectures for query resolution and routing
- Providing technical leadership to drive expertise and best practices across the ML discipline, mentoring others and leading by example
- Steering technical strategy in partnership with MLOps and backend engineering teams to enable rapid model iteration and optimization of the full ML lifecycle
You'll be embedded in cross-functional product squads working alongside product managers, data scientists, backend engineers, mobile and web engineers, designers, and operations specialists in an agile environment.
Ideal candidates have multiple years of track record developing and deploying advanced ML models in fast-moving tech companies, with production experience in deep learning, graph-based, and sequence-based architectures. You're impact-driven, owning the end-to-end journey from business problem to measurable production impact. You have a self-starter mindset, proactively identifying and tackling issues. You're proficient in production Python and SQL, comfortable with ambiguity, and have a product mindset focused on customer outcomes.
