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- Tasks: Design and deploy advanced machine learning systems while mentoring a team.
- Company: Leading AI firm in the UK driving innovation in financial services.
- Benefits: Competitive compensation, comprehensive benefits, and hybrid work options.
- Why this job: Lead cutting-edge AI projects and make a significant impact in the industry.
- Qualifications: Strong ML expertise with a Master's or PhD in a relevant field.
- Other info: Join a dynamic team focused on pushing the boundaries of AI technology.
The predicted salary is between 48000 - 72000 £ per year.
A leading AI firm in the United Kingdom is seeking a Staff Machine Learning Engineer (VP) to design and deploy advanced machine learning systems. You will lead the development of production-grade infrastructure and mentor a team of ML engineers. This hybrid role offers competitive compensation and a comprehensive benefits package while driving AI innovation in financial services.
Candidates should possess:
- Strong ML expertise
- A proven track record in the field
- A Master's or PhD in a relevant discipline
Staff ML Engineer - Production-Ready AI Platforms in London employer: TWG Global AI
Contact Detail:
TWG Global AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff ML Engineer - Production-Ready AI Platforms in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and ML space. Attend meetups, webinars, or conferences where you can chat with industry leaders and potential employers. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best machine learning projects. Whether it's a GitHub repo or a personal website, having tangible evidence of your expertise can really set you apart from the competition.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past projects in detail. Practice common ML interview questions and think about how you can demonstrate your leadership skills, especially if you're aiming for a senior role.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find the right opportunities. Plus, applying directly can sometimes give you an edge over other candidates. So, get your application in and let’s get you that dream job!
We think you need these skills to ace Staff ML Engineer - Production-Ready AI Platforms in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in machine learning and infrastructure development. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your background makes you the perfect fit for our team. Let us know what excites you about this opportunity!
Showcase Your Projects: If you've worked on any production-grade ML systems or have relevant projects, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions that demonstrate your expertise.
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 – just follow the prompts!
How to prepare for a job interview at TWG Global AI
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss your past projects in detail, especially those that involved designing and deploying production-grade systems. This is your chance to showcase your expertise!
✨Showcase Leadership Skills
Since this role involves mentoring a team, be prepared to talk about your leadership experiences. Think of examples where you've guided others or led a project. Highlight how you can inspire and elevate your team’s performance.
✨Understand the Company’s AI Vision
Research the company’s current AI initiatives, especially in financial services. Being able to discuss how your skills align with their goals will show that you’re genuinely interested and invested in their mission.
✨Prepare for Technical Challenges
Expect some technical questions or challenges during the interview. Practice coding problems or system design scenarios relevant to machine learning. This will help you demonstrate your problem-solving skills and readiness for real-world applications.
