Machine Learning Engineer, Cleo AI
+ Equity. Salary given is for the US
More information about location
AI personal finance assistant
Open for applications
AI personal finance assistant
201-500 employees
Open for applications
+ Equity. Salary given is for the US
More information about location
201-500 employees
Company mission
To change the world’s relationship with money.
Role
Who you are
- Excellent knowledge of both Data Science (Python, SQL) and production tools
- Experience building chat products
- A deep understanding of probability and statistics fundamentals
- Big picture thinking to correctly diagnose problems and productionising research
- Top tier communication skills, to be able to partner with Product and Commercial Leaders
- Industry-leading contributions to your field, communicated through conferences, blogs, talks, or open-source projects
- 3+ years of experience in data science, machine learning engineering, or related roles
- Excellent knowledge of both Data Science (python, SQL) and production tools
- Strong ability to communicate findings to non-technical stakeholders
- Experience deploying machine learning models into production; familiarity with Docker containers and container orchestration tools is a plus
What the job involves
- Machine Learning Engineers at Cleo work on building novel solutions to real-world problems
- This really does vary but could be: creating chatbots to coach our users around their financial health, creating classifiers to better understand transaction data or even optimising transactions within our payments platform
- You’ll be leading technical work within a team of adaptable, creative and product-focused engineers, who train & integrate cutting edge machine learning across a variety of products and deploy them into production for millions of users
- 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:
- Designed and implemented AI agents to analyse and extract insights from users’ transactional data
- Developed models to interpret transactional data, enhancing the understanding of users’ finances. Think about your bank statement—how often do you not recognise a transaction on first review?
- Created contextual intent classifiers to understand user conversations with Cleo, enabling tailored and accurate platform responses
- Engineered ML models to identify and deliver relevant actions to users within Cleo, ensuring a seamless, context-aware conversational experience
- Built models to evaluate risk in customer interactions with bank transaction features and user activities
- Developed optimisation models to improve payment success rates for customers while minimising business costs, tackling this as a two-sided optimisation challenge
- Whatever problem you tackle, and whichever team you join, your work will directly impact those most in need, helping to improve their financial health
Application process
- Interview with a Recruiter (30 mins)
- Interview with the Hiring Manager (30 mins)
- Technical Interview (45-60 mins)
- White-boarding session (60 mins)
- Technical Discussion (60 mins)
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
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
- No bullsh*t
- 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 AI
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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