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- Tasks: Lead the development of AI systems and design scalable ML infrastructure.
- Company: A leading AI company in the UK with a focus on innovation.
- Benefits: Unlimited annual leave, hybrid work model, and a fantastic benefits package.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: Strong Python skills, cloud experience, and knowledge of the ML lifecycle.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 48000 - 72000 £ per year.
A leading AI company in the United Kingdom is seeking a Senior Machine Learning Engineer to lead AI system development. This role involves designing and deploying scalable ML infrastructure while collaborating with cross-functional teams.
Ideal candidates will have:
- Robust Python skills
- Cloud platform experience
- A strong understanding of the machine learning lifecycle
A hybrid work model is offered with a great benefits package including unlimited annual leave.
Senior ML Engineer - Production AI (Hybrid) in England employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer - Production AI (Hybrid) in England
✨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 ML projects, especially those involving scalable infrastructure. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and cloud platform knowledge. Practice coding challenges and be ready to discuss your approach to the machine learning lifecycle.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities, and applying directly can sometimes give you a leg up. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Senior ML Engineer - Production AI (Hybrid) in England
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python prowess and any cloud platform experience you have. 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 with scalable ML infrastructure and how you've collaborated with cross-functional teams in the past.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon 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 this exciting opportunity!
How to prepare for a job interview at Faculty
✨Know Your ML Lifecycle
Make sure you can confidently discuss the machine learning lifecycle. Brush up on each stage, from data collection to model deployment. Being able to articulate your experience in these areas will show that you’re not just familiar with the theory but have practical knowledge too.
✨Showcase Your Python Skills
Prepare to demonstrate your Python expertise during the interview. Be ready to discuss specific projects where you've used Python for ML tasks. If possible, bring along examples of your code or projects to illustrate your capabilities.
✨Familiarise Yourself with Cloud Platforms
Since cloud platform experience is key for this role, make sure you know the ins and outs of the platforms you’ve worked with. Be prepared to discuss how you’ve deployed ML models in the cloud and any challenges you faced along the way.
✨Collaborate and Communicate
This role involves working with cross-functional teams, so be ready to talk about your collaboration experiences. Share examples of how you’ve effectively communicated complex technical concepts to non-technical stakeholders, as this will highlight your ability to work well in a team environment.
