At a Glance
- Tasks: Lead the scaling and optimisation of ML infrastructure for innovative AI/ML projects.
- Company: Recursion, a forward-thinking company focused on AI and machine learning.
- Benefits: Hybrid work model, competitive salary, and opportunities for mentorship and growth.
- Other info: Foster a model-driven culture while working with massive datasets.
- Why this job: Join a dynamic team and make a real impact in the AI/ML field.
- Qualifications: Experience in MLOps, distributed systems, and strong leadership skills.
The predicted salary is between 80000 - 100000 £ per year.
Recursion seeks an experienced technical lead to oversee the scaling and optimization of ML infrastructure within our London office. You will enable AI/ML teams to innovate and ensure that our models operate efficiently across massive datasets. This role includes mentoring and fostering a model-driven culture. The position combines a people-first mindset with deep technical skills in MLOps and distributed systems. A hybrid work model is in place, requiring office presence at least 50% of the time.
ML Infrastructure Lead – Scale & Deploy AI (Hybrid London) employer: Recursion
Recursion is an exceptional employer that prioritises a people-first culture while driving innovation in AI and ML. Located in the vibrant city of London, we offer a hybrid work model that promotes flexibility alongside collaboration, ensuring our employees thrive both personally and professionally. With ample opportunities for mentorship and growth, you will be part of a dynamic team dedicated to pushing the boundaries of technology in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land ML Infrastructure Lead – Scale & Deploy AI (Hybrid London)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI/ML space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects or contributions to open-source, make sure to highlight them during interviews. We want to see how you’ve tackled real-world problems in ML infrastructure.
✨Tip Number 3
Prepare for technical challenges! Brush up on your MLOps and distributed systems knowledge. We recommend practicing coding problems and system design scenarios that are relevant to the role.
✨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 take that extra step!
We think you need these skills to ace ML Infrastructure Lead – Scale & Deploy AI (Hybrid London)
Some tips for your application 🫡
Show Your Technical Skills:Make sure to highlight your experience with MLOps and distributed systems in your application. We want to see how your technical expertise aligns with the role, so don’t hold back on those details!
Emphasise Your People Skills:Since this role is all about mentoring and fostering a model-driven culture, let us know about your leadership experiences. Share examples of how you've supported teams or individuals in the past.
Tailor Your Application:Take a moment to customise your CV and cover letter for this specific role. We love seeing candidates who take the time to connect their skills and experiences directly to what we’re looking for.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to shine in front of our hiring team!
How to prepare for a job interview at Recursion
✨Know Your Tech Inside Out
Make sure you’re well-versed in MLOps and distributed systems. Brush up on the latest tools and technologies that are relevant to scaling ML infrastructure. Be ready to discuss specific projects where you've optimised models or improved efficiency.
✨Showcase Your Leadership Skills
Since this role involves mentoring, be prepared to share examples of how you've led teams or fostered a collaborative environment. Think about times when you’ve helped others grow or contributed to a model-driven culture.
✨Understand Their Needs
Research Recursion and their current projects. Understand their approach to AI/ML and think about how your experience aligns with their goals. This will help you tailor your answers and show that you’re genuinely interested in the role.
✨Prepare for Hybrid Work Questions
Since the position requires at least 50% office presence, be ready to discuss your thoughts on hybrid work. Share how you manage collaboration and communication in a hybrid setting, and why you believe it’s beneficial for team dynamics.
