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- Tasks: Lead the development and deployment of ethical AI systems with a focus on scalability.
- Company: A leading AI solutions company in Greater London with a diverse team.
- Benefits: Hybrid working options and a collaborative environment.
- Why this job: Make a positive impact through technology while working on cutting-edge AI projects.
- Qualifications: Experience in ML, software engineering, and strong Python skills.
The predicted salary is between 48000 - 72000 £ per year.
A leading AI solutions company in Greater London is looking for a Senior Machine Learning Ops Engineer to lead the development and deployment of ethical AI systems. This cross-functional role requires experience in ML, software engineering, and strong Python skills.
You will be responsible for designing scalable ML software and collaborating with various teams to solve client challenges. The position offers hybrid working options and a diverse team environment focused on positive impact through technology.
Senior ML Ops Engineer — Secure, Scalable AI Delivery in London employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Ops Engineer — Secure, Scalable AI Delivery in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community on LinkedIn or at local meetups. 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 that highlight your experience with ethical AI systems. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding the latest trends in ML Ops. Practice common interview questions and be ready to discuss how you've tackled challenges in previous roles.
✨Tip Number 4
Don’t forget to 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 about their job search!
We think you need these skills to ace Senior ML Ops Engineer — Secure, Scalable AI Delivery in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in ML and software engineering. We want to see how your skills align with the role, so don’t be shy about showcasing your Python prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re passionate about ethical AI systems and how you can contribute to our mission. Keep it engaging and relevant to the job description.
Showcase Your Projects: If you've worked on any interesting ML projects, make sure to mention them! We love seeing real-world applications of your skills, especially if they demonstrate your ability to design scalable solutions.
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 this exciting opportunity!
How to prepare for a job interview at Faculty
✨Know Your ML Fundamentals
Brush up on your machine learning concepts and frameworks. Be ready to discuss your experience with ethical AI systems and how you've implemented them in past projects. This will show that you’re not just familiar with the theory but can apply it practically.
✨Showcase Your Python Skills
Prepare to demonstrate your Python expertise. You might be asked to solve coding problems or explain your approach to building scalable ML software. Practising common algorithms and libraries like TensorFlow or PyTorch can give you an edge.
✨Collaboration is Key
Since this role involves working with various teams, be prepared to discuss your experience in cross-functional collaboration. Share examples of how you’ve successfully worked with different stakeholders to tackle client challenges and deliver impactful solutions.
✨Embrace the Hybrid Work Culture
Familiarise yourself with hybrid working dynamics. Be ready to discuss how you manage your time and productivity in a flexible work environment. Highlight any previous experiences that showcase your adaptability and commitment to teamwork, regardless of location.
