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- Tasks: Lead a team of ML engineers to develop and enhance Chat features.
- Company: Fast-growing fintech company based in London with a focus on innovation.
- Benefits: Competitive salary, flexible work arrangements, and great career growth.
- Why this job: Join a dynamic team and shape the future of customer interactions with AI.
- Qualifications: Proven experience in machine learning and team management, proficient in Python.
- Other info: Exciting opportunity in a collaborative environment with a focus on cutting-edge technology.
The predicted salary is between 48000 - 72000 £ per year.
A fast-growing fintech company in London is looking for a Machine Learning Team Lead to join their Chat data science function. This role involves managing a team of ML engineers, developing production models for the Chat feature, and improving customer behavior datasets.
The ideal candidate will have extensive experience in deploying machine learning models and managing teams, as well as proficiency in Python.
A competitive compensation package and flexible work arrangements are offered.
ML Engineering Manager for Chat & LLMs (Hybrid) employer: cleo
Contact Detail:
cleo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineering Manager for Chat & LLMs (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech and ML space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects or GitHub repos, make sure to highlight them. It’s a great way to demonstrate your expertise in deploying ML models.
✨Tip Number 3
Prepare for the interview by brushing up on team management scenarios. Be ready to discuss how you’ve led teams and tackled challenges in previous roles.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are excited about joining our team.
We think you need these skills to ace ML Engineering Manager for Chat & LLMs (Hybrid)
Some tips for your application 🫡
Show Off Your Experience: When you're writing your application, make sure to highlight your experience in deploying machine learning models and managing teams. We want to see how your background aligns with the role of ML Engineering Manager, so don’t hold back!
Tailor Your Application: Take a moment to customise your application for this specific role. Mention your proficiency in Python and any relevant projects you've worked on that relate to chat features or customer behaviour datasets. This helps us see why you’re the perfect fit!
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured applications that are easy to read. Use bullet points if necessary to break down your skills and experiences – it makes it easier for us to spot what we’re looking for!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at cleo
✨Know Your ML 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 knowledge and experience.
✨Showcase Your Leadership Skills
As a Machine Learning Team Lead, you'll need to demonstrate your ability to manage and inspire a team. Prepare examples of how you've successfully led projects or mentored team members in the past. Highlight your communication style and how you foster collaboration.
✨Familiarise Yourself with Chat Data Science
Since this role focuses on the Chat feature, brush up on the latest trends and technologies in chat data science and LLMs. Being able to discuss relevant advancements or case studies will impress your interviewers and show your enthusiasm for the field.
✨Prepare Questions About Company Culture
Understanding the company's culture is crucial, especially in a hybrid work environment. Prepare thoughtful questions about their team dynamics, remote work policies, and how they support professional development. This shows you're serious about finding a good fit for both you and the company.
