Machine Learning Engineer (Research)
LondonInsight – Data Analytics /Full Time /HybridApply for this jobAbout MoneyboxAt Moneybox, we believe that building wealth throughout life, and all of the freedom, opportunities, and peace of mind that come with it, should be possible for everyone.We launched in 2016 with our now-famous round-ups feature, and helped thousands of people start investing with just their spare change. Fast forward to today, and we’re now helping more than 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, our customers are guaranteed a service they can rely on, that supports them through every step, and celebrates with them along the way.While Moneybox is a wealth management platform, we’re guided by our belief that wealth isn’t about the money. It’s about the means to more – more freedom and possibility, more opportunities and more peace of mind.Job BriefIn the next chapter of Moneybox - we are building a comprehensive AI system - Moneybox Aurora - that helps guide users to achieve more, and to have confidence and peace of mind while doing it. The machine learning team sits at the forefront of this development. We develop both the ML models that power the “brain” of Aurora, but we also build the core decisioning frameworks that guide our users and ensure our systems are safe, reliable, and act in their best interests.The core ML problem we have is tied to guiding the customer to the right solution. It encompasses many problem sets, e.g. NLP, recommendation systems and symbolic reasoning using specifically trained SLM’s.We host all of our models internally. We develop using Databricks@Azure, and we deploy through Databricks, or directly on Azure Kubernetes Service (AKS).This role will work very closely with our ML researchers and data scientists, to productionise code, streamline solutions and create efficient deployment packages. You'll be the bridge between cutting-edge research and production systems, translating research prototypes into robust, scalable, and maintainable products.
What you’ll do
You will work with other ML researchers, data scientists and ML engineers to: Help deploy production-ready code from other ML engineers and ML researchers and provide guidance in deployable code best practices Work with ML researchers to identify and engineer efficient deployment patterns for deep learning models Help prepare the data, restructure it and ensure good contracts with the BE teams on the interfaces where they are requesting ML inference Choose inference frameworks and help productionise solutions in an efficient manner Learn and evolve - we’re keeping at the cutting edge of what current DL and LLM research provides - we expect you to learn and evolve with us Work with the AI and decisioning team and Director of AI and Decision Intelligence to input into choices on objective functions, content strategy and wider data strategy to ensure good long-term ML outcomes
Who you are
Have experience in deploying production-ready solutions into production, serving at scale of millions of users Enjoy solving tough problems, especially cold start problems and applying out-of-the-box thinking to combine ML and computer science to solve tangible problems Are a systems thinker and enjoy figuring out a scalable solution that can fit an emerging system Thrive in a fast-paced startup environment Eager to learn new things and challenge your existing frameworks Are not scared of ambiguity
Experience and skills – Essential
1 year of industry experience working in an MLE, ML research or Data Science role with applicable engineering skills Experienced Python programmer with 2+ years of programming experience in a day-to-day ML setting Experience with PyTorch and / or other DL frameworks Experience with applying deep learning or deep probabilistic modelling solutions to business problems, and have launched them in production Experienced with Git or other version control systems Good understanding of core machine learning concepts Demonstrated ability to learn quickly and apply learned knowledge - either in academic or professional settings
Experience and skills – not essential for the role, but will be counted as a plus
Industrial experience with LLM’s, in particular: Any experience fine-tuning OSS LLM’s Experience in LLM distillation Experience in using LangChain or associated frameworks to orchestrate LLM workloads Experience with Bayesian networks and deep probabilistic models Experience with deploying to Azure AKS Experience with Databricks Good interpersonal skills and experience working with varied engineering backgrounds to interface ML with other system components
What’s in it for you?
Opportunity to join a fast-growing, award-winning and super ambitious business. 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. Competitive remuneration package. Company shares Company pension scheme Hybrid working environment (Our office is in London, by the Oxo Tower) 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 25 days holiday + bank holidays with additional days added with length of service.
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 potentialWorking 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!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.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.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 rather we did not keep your details on file, you can contact us at email: application will be subject to criminal record and adverse credit history checks (such as CCJs, IVAs and bankruptcy). 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.Apply for this job
