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: Collaborative environment with a focus on innovation and model-driven culture.
- Why this job: Join a dynamic team and make a real impact in the AI/ML landscape.
- Qualifications: Experience in MLOps, distributed systems, and a passion for mentoring others.
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 help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects and contributions to ML infrastructure. This is your chance to demonstrate your expertise and passion for the field, so make it shine!
✨Tip Number 3
Prepare for those interviews! Research common questions related to MLOps and distributed systems, and practice your answers. We want you to feel confident and ready to impress the hiring team with your knowledge.
✨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 ML Infrastructure Lead – Scale & Deploy AI (Hybrid London)
Some tips for your application 🫡
Show Your Passion for AI/ML:When writing your application, let your enthusiasm for AI and ML shine through. We want to see how your passion aligns with our mission at Recursion, so share any relevant projects or experiences that highlight your love for the field.
Highlight Your Technical Skills:Make sure to showcase your deep technical skills in MLOps and distributed systems. We’re looking for someone who can lead and innovate, so don’t hold back on detailing your expertise and any specific tools or technologies you’ve worked with.
Emphasise Your People-First Mindset:Since this role involves mentoring and fostering a model-driven culture, it’s crucial to convey your people-first approach. Share examples of how you’ve successfully led teams or mentored others in the past, as we value collaboration and support.
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’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values!
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.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Practice articulating how you would handle challenges related to scaling AI/ML models or managing large datasets. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Embrace the Hybrid Work Model
Since the position requires at least 50% office presence, be ready to discuss how you manage remote and in-office work effectively. Share your thoughts on maintaining team cohesion and productivity in a hybrid setting.
