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- Tasks: Lead the design and development of cutting-edge machine learning platforms.
- Company: Fast-scaling AI organisation in the heart of London.
- Benefits: Hybrid work model, competitive salary, and opportunities for mentorship.
- Other info: Collaborative environment with great potential for career growth.
- Why this job: Join a dynamic team and shape the future of scalable AI solutions.
- Qualifications: Strong experience in machine learning and proficiency in Python required.
The predicted salary is between 80000 - 100000 £ per year.
Xcede is seeking a senior-level technical leader to join a fast-scaling AI organization in London. The role involves leading the design and development of machine learning platforms, collaborating across teams to deliver scalable ML solutions, and mentoring engineers.
Candidates should have strong experience in machine learning engineering, proficiency in Python, and familiarity with tools like Docker and Kubernetes.
The position operates on a hybrid model, requiring attendance in the London office 2 days a week.
Lead ML Engineer: Scalable AI Platform (Hybrid London) employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead ML Engineer: Scalable AI Platform (Hybrid London)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible evidence of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge, especially around Python, Docker, and Kubernetes. Practice common ML engineering questions and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly can sometimes give you a better chance of getting noticed.
We think you need these skills to ace Lead ML Engineer: Scalable AI Platform (Hybrid London)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience in machine learning engineering and your proficiency in Python. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Take a moment to customise your application for this specific role. Mention your familiarity with tools like Docker and Kubernetes, and how you've used them in past projects. It helps us see you as a great fit!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to understand your background and what you bring to the table.
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’s super easy!
How to prepare for a job interview at Xcede
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and frameworks. Be ready to discuss your past projects in detail, especially those involving scalable solutions. We recommend preparing examples that showcase your proficiency in Python and any relevant tools like Docker and Kubernetes.
✨Show Your Leadership Skills
As a Lead ML Engineer, you'll need to demonstrate your ability to lead and mentor. Think of specific instances where you've guided a team or influenced project outcomes. We suggest preparing anecdotes that highlight your leadership style and how you foster collaboration across teams.
✨Get Familiar with the Company
Research Xcede and their AI initiatives. Understanding their mission and recent projects can give you an edge. We advise you to align your experiences with their goals and be ready to discuss how you can contribute to their fast-scaling environment.
✨Prepare for Hybrid Work Questions
Since this role operates on a hybrid model, be prepared to discuss your approach to remote collaboration and in-office work. We suggest thinking about how you manage communication and productivity in a hybrid setting, as this will show your adaptability and readiness for the role.