Job Description
About Moneybox
At Moneybox, our mission is to give everyone the means to get more out of life. We’re guided by our belief that wealth isn’t about the money, it’s about the means to more - more freedom, opportunities, possibilities, and peace of mind. Moneybox is an award-winning wealth management platform, helping over one and a half million people build wealth throughout their lives, whether they’re saving and investing, buying their first home, or planning for retirement.
Job Brief
We are building Aurora, an AI system designed to guide customers toward better financial outcomes. The core technical challenge is hard: given a customer with incomplete, uncertain information about their own financial situation and goals, how do you reliably converge on the right guidance - at scale, in a regulated environment, with decisions that must be auditable and traceable?
This breaks into several non-trivial subproblems. How do you efficiently resolve uncertainty about customer state through active information gathering, asking the right question at the right moment rather than exhausting the user? How do you translate natural language policy and regulatory constraints into formal optimisation logic that is both correct and inspectable?
How do you orchestrate learned and symbolic components such that the overall system behaves reliably, degrades gracefully, and can be reasoned about by humans? How do you do all of that without paying the engineering overhead on the expert parts of the system?
We have working hypotheses and committed architectural directions on all of these. We also change our minds quickly when presented with strong arguments or new evidence. If you think we’re wrong about something, we want to know.
We host most of our models internally. We develop using Databricks@Azure, and we deploy through Databricks, or directly on Azure Kubernetes Service (AKS).
This is the foremost research position in the ML team. You will report directly to the Director of AI and Decision Intelligence and work alongside a principal data scientist, senior ML engineer, senior data scientist, and two ML engineers.
What you’ll do
- You will work with other ML researchers, data scientists and ML engineers to:
- Propose and prototype architectures that address our core problem set, with clear-eyed assessments of engineering complexity and scalability tradeoffs
- Code proofs of concept to validate hypotheses and test the limits of theoretical approaches, grounded in empirical reality rather than theory alone
- Serve as the team’s research lead - setting the intellectual agenda, running literature reviews, and keeping the team calibrated to what is actually state of the art versus what is hype
- Challenge existing architectural decisions, including ones we are currently confident about
- Input information to the Director of AI and Decision Intelligence and the wider AI team for decisions on objective functions, data strategy, and content strategy to ensure long-term coherence between research direction and overall system goals
- Collaborate with academic partners where relevant and possible, with scope to contribute to publishable work emerging from applied research
Who you are
- You think in systems - you can hold the interaction between components in your head, reason about failure modes, and identify where theoretical elegance will break against production constraints
- You have an optimisation mindset, not just in the technical sense but in how you approach problems generally - you look for the lever, not the brute force solution
- You are comfortable with high autonomy and wide scope in a fast-paced environment
- You deliver great results while managing your own pace sustainably
- You read the literature seriously, have opinions about it, are willing to defend them, and willing to update them
- You are not scared of ambiguity and thrive more when the problem is harder than when the solution space is clear
Experience and skills – essential
- 3+ years in an ML research or engineering role with meaningful exposure to text generation, agentic systems, or symbolic reasoning (one of is fine) - or equivalent academic experience with real applied components
- Demonstrated ability to prototype rapidly and evaluate results honestly
- Knowledge of applied machine learning, model tuning and model evaluation
- Knowledge of the latest approaches in generative AI, including SoTA models
- Familiarity with open-source LLM ecosystems and cloud infrastructure sufficient to bootstrap independently
Experience and skills – not essential for the role, but will be counted as a plus
- Experience combining deep learning with formal or symbolic systems - this is the closest to what we are building and the strongest signal we can receive from a candidate
- Familiarity with probabilistic graphical models or decision-theoretic frameworks
- Experience in regulated or high-stakes deployment environments
- Working in a scaled B2C environment
- Experience deploying using any of: Databricks, Azure or MLflow
- Research and building of foundational ML models, regardless of domain
- A genuine interest in AI safety and the ability to reason carefully about systemic risk
What’s in it for you?
Opportunity to join a fast-growing, award-winning and super ambitious company
Work with a friendly team of highly motivated individuals
Be in an environment where you are listened to and can actually have an impact
Thriving collaborative and inclusive company culture
Company bonus scheme
Company pension scheme
Home office furniture allowance
Personal Annual Learning and Development budget
Private Medical Insurance
Health Cash Plan (cashback on visits to the dentist & opticians etc)
Cycle to work scheme
Gympass subscription to a variety of gyms and wellbeing apps
Enhanced parental pay & leave
Hybrid working environment (2 days in our London office)
25 days holiday + bank holidays with additional days added with length of service.
Our office is in London, by the Oxo Tower
Our Commitment to DE&I:
At Moneybox, we promote, support and celebrate inclusion, diversity and equity for all, so that everyone can bring their full selves to work. We believe that diversity drives innovation, and that if our team is representative of our community of customers, we can better support their needs. To ensure our recruitment processes provide an equal opportunity for all applicants to succeed, we encourage you to let us know if there are any adjustments that we can make. We are open-minded and always willing to go the extra mile to ensure all applicants can present their full self and potential
Working Policy:
We have a hybrid policy that includes 2 days from our London office and 3 from home. If the role states it is either hybrid or remote candidates must be based within the UK.
Visa Sponsorship:
At this time we cannot offer visa sponsorship for this role and we cannot consider overseas applications.
Please read before you apply!
Please note if offered a position, the offer is conditional and subject to the receipt of satisfactory pre-employment checks which we will conduct such as criminal record and adverse credit history checks. As a regulated financial business, an adverse financial history could impact your suitability for the role. If you are aware of anything that could affect your suitability for the role, please let us know in advance.
By sending us your application you acknowledge and agree to Moneybox using your personal data as described below.
We collect applicants’ personal data to manage our recruitment related activities. Consequently, we may use your personal data to evaluate your application, to select and shortlist applicants, to set up and conduct interviews and tests, to evaluate and assess the results, and as is otherwise needed in the recruitment process generally.We do not share your personal data with unauthorised third parties. However, we may, if necessary, share your personal data to carefully selected third parties acting on our behalf. This may include transfers to servers and databases outside the country where you provided us with your personal data. Such transfers may include for example transfers and/or disclosures outside the European Economic Area and in the United States of America.
If you are unsuccessful in your application, we may keep your details on file so that we can tell you about other suitable vacancies which may be of interest to you when they arise in the future.
If you would like to reach us then please email: [email protected]
If you would rather we did not keep your details on file, you can contact us at: [email protected]
