Role overview
- 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 we're looking for
- 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
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]