At a Glance
- Tasks: Build and improve cutting-edge ML systems while mentoring a small team.
- Company: Dynamic fintech company in Central London with a focus on innovation.
- Benefits: Competitive salary, stock options, private medical insurance, and free gym access.
- Other info: Enjoy a vibrant office culture with social events and wellness perks.
- Why this job: Join a hands-on role with growth potential into management while shaping the future of ML.
- Qualifications: Strong ML engineering background and desire to lead a team.
The predicted salary is between 110000 - 110000 € per year.
We’re looking for a Machine Learning Lead Engineer who wants to operate as a player‑coach — someone still very hands‑on, but excited to grow into a proper management role over time. This is not a pure manager role from day one. You’ll be building, shipping, and improving ML systems while gradually taking on more team leadership responsibilities.
Department: Platform
Location: London
Compensation: £110,000 / year
Key Responsibilities:
- Build and maintain production‑grade ML systems and pipelines
- Stay hands‑on (coding, reviews, debugging, deployments)
- Mentor a small team of ML engineers (2–3 people initially)
- Establish ML engineering & MLOps best practices
- Improve deployment, monitoring, and model lifecycle management
- Collaborate with DS, Risk, Product, and Engineering
- Help shape roadmap and hiring
Skills, Knowledge & Expertise:
- Strong background as an ML Engineer (not purely DS/research)
- Experience deploying and running ML models in production
- Solid software engineering skills (Python, APIs, systems)
- Good understanding of MLOps stack (CI/CD, monitoring, pipelines)
- Familiarity with tools like MLflow, Airflow, Evidently, DVC, Docker, Kubernetes
- Cloud experience (AWS/GCP/Azure)
- Some mentoring/leadership experience + desire to grow into management
Nice to have:
- Experience scaling ML platforms or teams
- Fintech / lending / risk domain exposure
Job Benefits:
- Stock Options
- Private Medical insurance via Vitality and Dental Insurance with BUPA
- EAP with Health Assured
- Enhanced Maternity and Paternity Leave
- Modern and sophisticated office space in Central London
- Free Gym in office building in Holborn
- Subsidised Lunch via Feedr
- Deliveroo Allowance if working late in office
- Monthly in office Masseuse
- Team and Company Socials
- Football Power League / Paddle and Yoga Club
Lead Machine Learning Engineer employer: YouLend
Join a forward-thinking company in the heart of London, where innovation meets collaboration. As a Lead Machine Learning Engineer, you'll not only enhance your technical skills but also have the opportunity to mentor a talented team while enjoying a vibrant work culture that prioritises employee well-being and growth. With benefits like stock options, private medical insurance, and a modern office environment, this role offers a rewarding career path in a dynamic fintech setting.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the machine learning field and let them know you're on the lookout for opportunities. You never know who might have a lead or can refer you to a position that’s not even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that highlight your hands-on coding and deployment experience. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and leadership questions. Since this role is about being a player-coach, be ready to discuss how you’ve mentored others and your approach to team collaboration.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Lead Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Lead Machine Learning Engineer role. Highlight your hands-on coding experience and any leadership roles you've had, even if they're small.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about this position. Share your passion for ML systems and how you envision growing into a management role while still being hands-on.
Showcase Your Projects:Include links to any relevant projects or GitHub repositories that demonstrate your expertise in ML engineering and MLOps. We love seeing practical examples of your work!
Apply Through Our Website:We encourage you to apply directly through our website. 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 YouLend
✨Know Your ML Stuff
Make sure you brush up on your machine learning fundamentals and be ready to discuss your hands-on experience with building and deploying ML systems. Be prepared to share specific examples of projects you've worked on, especially those that highlight your coding skills and familiarity with tools like Docker and Kubernetes.
✨Show Your Leadership Potential
Even though this role isn't purely managerial from the start, it's important to demonstrate your mentoring experience. Think of instances where you've guided others or taken the lead on a project. Highlight your desire to grow into a management role and how you plan to support your future team.
✨Understand MLOps Best Practices
Familiarise yourself with MLOps concepts and be ready to discuss how you've implemented best practices in your previous roles. Talk about your experience with CI/CD pipelines, monitoring, and model lifecycle management, as these are crucial for the position.
✨Be Ready to Collaborate
This role involves working closely with various teams, so be prepared to discuss how you've successfully collaborated with data scientists, product managers, and engineers in the past. Share examples of how you’ve contributed to cross-functional projects and how you can help shape the roadmap moving forward.
