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- Tasks: Lead innovative AI projects and design scalable machine learning systems.
- Company: Join a forward-thinking tech company in Greater London.
- Benefits: Unlimited leave, private healthcare, and hybrid working model.
- Other info: Exciting opportunity for career growth in a dynamic environment.
- Why this job: Shape the future of AI while mentoring talented engineering teams.
- Qualifications: Strong Python skills and experience with ML frameworks and Cloud platforms.
The predicted salary is between 70000 - 90000 £ per year.
Faculty is seeking a Lead Machine Learning Engineer in Greater London to spearhead technical direction and delivery of innovative AI projects. This role involves designing and maintaining scalable systems, guiding complex ML projects, and mentoring engineering teams.
Key qualifications include:
- Strong Python skills
- Experience with frameworks like Scikit-learn and TensorFlow
- Understanding of major Cloud platforms
Faculty offers an unlimited leave policy, private healthcare, and a hybrid working model.
Lead ML Engineer & Technical Architect (Hybrid) employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead ML Engineer & Technical Architect (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those using Python and frameworks like Scikit-learn or TensorFlow. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding cloud platforms. Practice common ML problems and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lead ML Engineer & Technical Architect (Hybrid)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your strong Python skills and experience with frameworks like Scikit-learn and TensorFlow. We want to see how you can bring your technical expertise to the table!
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific requirements of the Lead ML Engineer role. We love seeing how you connect your experience to what we’re looking for.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your qualifications and experiences.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Faculty
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and get familiar with frameworks like Scikit-learn and TensorFlow. Be ready to discuss your past projects in detail, especially how you designed scalable systems and tackled complex ML challenges.
✨Showcase Your Leadership Skills
Since this role involves mentoring engineering teams, be prepared to share examples of how you've guided others in previous roles. Highlight any experiences where you led a project or helped a team overcome technical hurdles.
✨Understand the Cloud Landscape
Familiarise yourself with major Cloud platforms, as they are crucial for this position. Be ready to discuss how you've used these platforms in your work and how they can enhance AI project delivery.
✨Ask Insightful Questions
Prepare thoughtful questions about Faculty's AI projects and their vision for the future. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values, especially regarding their unlimited leave policy and hybrid working model.