At a Glance
- Tasks: Lead innovative ML projects that tackle real-world problems and enhance user experiences.
- Company: Join Cleo, a forward-thinking company revolutionising financial health through AI.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: We celebrate diversity and encourage applications from all backgrounds.
- Why this job: Make a tangible impact by developing cutting-edge AI solutions that help millions.
- Qualifications: 5+ years in ML engineering, strong Python and SQL skills, and leadership experience.
The predicted salary is between 70000 - 90000 £ 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
- 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 ML Engineer — Production AI & LLMs employer: Cleo AI
Cleo is an exceptional employer for those passionate about machine learning and AI, offering a dynamic work culture that fosters creativity and collaboration. With a strong commitment to diversity and inclusion, employees are encouraged to bring their unique perspectives to the table, while also benefiting from ample opportunities for professional growth and development. Located in a vibrant tech hub, Cleo provides a stimulating environment where innovative solutions to real-world problems are at the forefront of its mission.
StudySmarter Expert Advice🤫
We think this is how you could land Lead ML Engineer — Production AI & LLMs
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving LLMs. This will not only demonstrate your expertise but also give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and SQL skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are genuinely interested in joining our team. Plus, it gives you a better chance of standing out!
We think you need these skills to ace Lead ML Engineer — Production AI & LLMs
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead ML Engineer role. Highlight your experience with deploying machine learning models and any relevant projects you've led. We want to see how your skills match up with what we're looking for!
Showcase Your Skills:Don’t forget to showcase your technical skills, especially in Python, SQL, and any production tools you’ve used. If you’ve worked with LLMs or Docker, make that clear! We love seeing how you can bring your expertise to our team.
Communicate Clearly:Remember, you’ll need to communicate findings to non-technical stakeholders. Use clear and concise language in your application to demonstrate your ability to break down complex concepts. We appreciate straightforward communication!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and we can’t wait to see your application come through. Let’s get started on this journey together!
How to prepare for a job interview at Cleo AI
✨Know Your Models Inside Out
Make sure you can discuss the machine learning models you've deployed in detail. Be ready to explain your decision-making process, the challenges you faced, and how you overcame them. This will show your depth of experience and understanding.
✨Communicate Like a Pro
Since you'll need to explain complex concepts to non-technical stakeholders, practice simplifying your explanations. Use analogies or real-world examples to make your points clear. This will demonstrate your ability to bridge the gap between technical and non-technical teams.
✨Showcase Your Leadership Skills
Prepare to discuss your experience leading projects. Highlight how you developed roadmaps, coordinated with team members, and reported progress. This will illustrate your capability to manage teams and drive projects forward effectively.
✨Familiarity with Tools is Key
If you have experience with Docker or container orchestration tools, be sure to mention it. Even if it's not a requirement, showing familiarity with these technologies can set you apart and demonstrate your readiness to tackle the role's challenges.
