At a Glance
- Tasks: Lead innovative machine learning projects that tackle real-world problems and enhance user experiences.
- Company: Join Cleo, a forward-thinking company revolutionising financial health through AI.
- Benefits: Competitive salary, inclusive culture, flexible working, and opportunities for professional growth.
- Other info: We celebrate diversity and encourage applications from all backgrounds.
- Why this job: Make a meaningful impact by shaping the future of AI in finance.
- Qualifications: 5+ years in machine learning, strong communication skills, and experience leading teams.
The predicted salary is between 80000 - 100000 £ per year.
Requirements
- Experience deploying multiple machine learning models into production
- 5+ years of experience in data science, machine learning engineering, or related roles
- Experience integrating and evaluating LLMs
- Excellent knowledge of both Data Science (Python, SQL) and production tools
- Understanding of probability and statistics fundamentals
- Strong ability to communicate findings to non-technical stakeholders
- Experience of leading projects involving multiple people including developing a short term roadmap and reporting progress
- Comfortable breaking down work incrementally
- (Desirable) Familiarity with Docker containers and container orchestration tools
- (Desirable) Experience with LLM-as-a-judge and/or annotation pipelines
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. They train, deploy, and improve machine learning models in production, ensuring they deliver meaningful impact for our users.
We’re looking for our next Lead Machine Learning Engineer to join our Chat Evaluations team. You’ll shape & guide technical work within a team of adaptable, creative and product-focused engineers, who deliver ML/AI features that improve the observability of chatbot quality and power the AI development cycle.
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:
- Deployed best-in-class credit decisioning models which affect millions of customers, using open banking data rather than traditional credit scoring
- 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?
- Fed user interaction data into fine-tuned LLMs and contextual ranking models, so Cleo knows how to start and continue an engaging conversation
- Developed optimisation models to improve payment success rates for customers while minimising business costs, tackling this as a two-sided optimisation challenge
- Designed and implemented AI agents to analyse and extract insights from users’ transactional data
Lead Machine Learning Engineer (Chat) employer: Cleo AI
Cleo is an exceptional employer that fosters a vibrant and inclusive work culture, where creativity and innovation thrive. As a Lead Machine Learning Engineer, you will have the opportunity to work on impactful projects that enhance financial health for users while collaborating with a diverse team of talented engineers. With a strong commitment to employee growth and development, Cleo offers a supportive environment that encourages continuous learning and the exploration of cutting-edge technologies.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Machine Learning Engineer (Chat)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself and make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to machine learning. Mock interviews with friends or using online platforms can help you feel more confident and ready to impress.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications from talented individuals like you. Tailor your application to highlight how your experience aligns with the role, and let us know why you're excited about joining our team.
We think you need these skills to ace Lead Machine Learning Engineer (Chat)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the specific skills and experiences mentioned in the job description. Highlight your experience with machine learning models, data science, and any relevant projects you've led. We want to see how you fit into our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background aligns with our mission at StudySmarter. Don’t forget to mention any experience with LLMs or production tools.
Showcase Your Communication Skills:Since you'll be communicating findings to non-technical stakeholders, make sure to demonstrate your ability to explain complex concepts simply. We love candidates who can bridge the gap between tech and everyday language!
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Cleo AI
✨Know Your Models Inside Out
Make sure you can discuss your experience deploying machine learning models in detail. Be ready to explain the challenges you faced and how you overcame them, especially with LLMs. This shows you not only understand the theory but also the practical application.
✨Brush Up on Your Tech Skills
Since the role requires excellent knowledge of Python and SQL, ensure you're comfortable discussing your coding experience. Prepare to solve a coding challenge or answer technical questions that demonstrate your proficiency in these languages.
✨Communicate Like a Pro
You’ll need to explain complex concepts to non-technical stakeholders, so practice simplifying your explanations. Think of examples from your past work where you successfully communicated findings and how it impacted decision-making.
✨Show Your Leadership Skills
Be prepared to talk about your experience leading projects and teams. Highlight how you developed roadmaps, managed progress, and collaborated with others. This will show that you’re not just a tech whiz but also a great team player and leader.
