Graduate Machine Learning Engineer, Cleo
£36.3-73.5k
+ Equity
More information about location
AI personal finance assistant
Open for applications
AI personal finance assistant
201-500 employees
Open for applications
£36.3-73.5k
+ Equity
More information about location
201-500 employees
Company mission
To help millions of people improve their financial health, and relate to them in a way their banks never could.
Role
Who you are
- Firstly and most importantly, all of the above sounds exciting to you and you want to make a positive difference in society by improving the financial health of our users worldwide
- You’ve also read our company values which drive our ways of working and help us deliver working software to our users, learn what works and iterate quickly to improve it. You are excited to learn how to embrace these opinions and use them to deliver value
- As this is a junior position we’re looking for someone who has recently graduated with a Computer Science / ML / AI related degree and Masters or a PhD
What the job involves
- Joining a cross-functional product squad with a mix of backend engineers, data analysts, frontend engineers, user researchers, designers, UX writers and others to develop features that improve our users’ financial health
- You will be building ML models to solve customer problems across chat, payments, risk and marketing. Supported by Senior ML engineers to help you craft the problem definition, modelling approach, and deployment options
- Deploy these models into our production environments using our in-house ML platform, that you can read about on our blog. Let's have an Espresso: MLOps at Cleo
- Integrating LLMs where appropriate, following evaluation-driven development of applied AI
- Learning not only how to deploy and build models, but how to understand data, business problems and how you know what you have built works for customers
- Learning how to manage and own ML in production with our monitoring tools for; feature drift, accuracy and performance of your APIs
- Learning about our approach to data-driven development where we emit data with each feature we build so we can measure what it’s doing, and finding out how we analyse that data to detect problems and come up with new ideas
- Here are some examples, big and small, of the kinds of product feature work our ML Engineers have taken part in over the last year:
- Built ML models to understand the risk of customers using complex transactional bank data and user activity
- Built models to optimise the payment success for our customers and optimising the costs for the business. Think of this as a two-sided optimisation problem
- Building AI Agents to explore and derive insights from users transactional data
- Developed deeper understanding of users finances through models extracting meaning from transactional data. Think about your bank statement, how often do you not know what a transaction is?
- Developed contextual intent classifiers to understand what conversations users are having with Cleo and control how Cleo should respond
- Building models to understand the actions that users have available to them in Cleo and provide those contextually in conversations
- Whichever squad and part of the business you land in, you will ship changes to our millions of active users and see your work having a material impact on the financial health of those most in need
Salary benchmarks
Our take
People are increasingly not satisfied with the products being offered by traditional banks, which have proven slow to react to the needs of younger consumers who expect more from their everyday experiences.
Cleo was one of the first companies to make great use of chatbots that sit within Facebook's messenger app. This chatbot-first approach and Gen Z user base have given it strong virality. It now has millions of registered users, 99% of which are based in the US, leading to a decision to take a year break from the UK market to focus on its US Gen Z customers. And after a successful year in the US its now eyeing up a return to the UK.
Its Series C funding will help the company to double down in the US, where it will make a significant increase in employee headcount, and enable Cleo to maintain and expand its service during an economic downturn.
Financial advice delivered via bots is a crowded space, so Cleo benefits from having a strong brand presence. It has gone for very bold, fun, Gen Z-focused messaging which helps it to stand out from competitors such as Emma, Plum, and Chip.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Employee endorsements
Nice people
"Cleople are unmatched. The vibes, the energy, the friendships. I genuinely love my colleagues and have developed real-life friendships. I don't know..."
Funding (last 2 of 5 rounds)
Jun 2022
$80m
SERIES C
Dec 2020
$44m
SERIES B
Total funding: $137.5m
Company benefits
- Learning and development
- Mental health support
- Agile working
Company values
- Make it Happen
- Learn at Speed
- Bring Good Vibes
Company HQ
London, UK
Leadership
Barnaby Hussey-Yeo
(Founder & CEO)Previously a Data Scientist at Wonga, one of the companies that pioneered the smart use of data for loan decisions. Joined Entrepreneur First where Cleo was formed.
Diversity, Equity & Inclusion at Cleo
Annie Jackson (Head of Talent )
- We’ve set up an internal committee of truly passionate people that are dedicated to ensuring Diversity and Inclusion is embedded in how we all operate as a team. We agree on meaningful actions, and get on with implementing them. We have three main focuses right now, which are:
- 1) Improving SocioEconomic diversity across the company
- 2) Increasing the number of women in Leadership roles
- 3) More community outreach
- Check out our 2022 Diversity and Inclusion report, here: https://web.meetcleo.com/blog/cleo-diversity-equity-and-inclusion-report-2022
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