At a Glance
- Tasks: Lead AI strategy and develop robust ML systems from exploration to deployment.
- Company: EDITED, a forward-thinking tech company in Greater London.
- Benefits: Flexible working environment with remote options and competitive salary.
- Other info: Join a dynamic team with opportunities for professional growth.
- Why this job: Make a real impact in AI while mentoring the next generation of engineers.
- Qualifications: Master's or PhD in Computer Science, strong Python skills, Docker and Kubernetes experience.
The predicted salary is between 70000 - 90000 € per year.
EDITED, located in Greater London, is seeking a Staff Machine Learning Engineer to spearhead their AI strategy and develop robust ML systems. You will take ownership of the entire ML lifecycle, from initial exploration to deployment.
Responsibilities include:
- Leading MLOps
- Mentoring junior engineers
- Collaborating with product teams
A Master's or PhD in Computer Science is required, along with strong Python proficiency and experience with Docker and Kubernetes. Enjoy a flexible working environment with remote options.
Staff ML Engineer: AI Systems & MLOps Lead in London employer: Edited
EDITED is an exceptional employer located in Greater London, offering a dynamic and flexible working environment that fosters innovation and collaboration. As a Staff Machine Learning Engineer, you will have the opportunity to lead cutting-edge AI initiatives while mentoring junior engineers, ensuring your professional growth in a supportive culture. With remote work options and a commitment to employee development, EDITED stands out as a rewarding place for those seeking meaningful contributions in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Staff ML Engineer: AI Systems & MLOps Lead in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry 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 ML projects and contributions. We want to see your work in action, so don’t be shy about sharing your GitHub or any relevant demos.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your experience with MLOps, Docker, and Kubernetes. We recommend doing mock interviews to build your confidence.
✨Tip Number 4
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 and eager to join our team.
We think you need these skills to ace Staff ML Engineer: AI Systems & MLOps Lead in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your Python proficiency and any experience you have with Docker and Kubernetes. 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 CV and cover letter for this specific role. Mention your experience in leading MLOps and mentoring junior engineers, as these are key aspects of the job we’re looking to fill.
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to read and get straight to the point about your qualifications and experiences.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Edited
✨Know Your ML Lifecycle
Make sure you can confidently discuss the entire machine learning lifecycle. Be prepared to explain your experience with each stage, from data exploration to deployment. This will show that you understand the complexities involved and can take ownership of the process.
✨Show Off Your Python Skills
Since strong Python proficiency is a must, brush up on your coding skills before the interview. Be ready to solve problems or even write code on the spot. Practising common algorithms and libraries used in ML can give you an edge.
✨Familiarise Yourself with MLOps Tools
Get comfortable discussing Docker and Kubernetes, as these are key tools for MLOps. You might be asked about your experience using them, so have specific examples ready. If you’ve led projects using these technologies, highlight those experiences.
✨Mentorship Mindset
As mentoring junior engineers is part of the role, think about your past experiences in guiding others. Prepare to share examples of how you've supported team members in their growth, as this will demonstrate your leadership capabilities.
