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- Tasks: Lead the transition of ML models into production-grade services and manage AI-related cloud spending.
- Company: Join a cutting-edge tech recruitment platform in vibrant Newcastle upon Tyne.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact by enhancing deployment capabilities and overseeing the entire ML lifecycle.
- Qualifications: Proficiency in software engineering, REST APIs, and cloud environments, especially AWS.
- Other info: Collaborate with data science teams in a dynamic and innovative environment.
The predicted salary is between 48000 - 72000 £ per year.
A tech recruitment platform is seeking a Senior ML Engineer in Newcastle upon Tyne to lead the transition of experimental models into production-grade services. This hybrid role demands proficiency in software engineering fundamentals, REST APIs, and operational backend services in cloud environments, primarily AWS.
The successful candidate will oversee the entire ML lifecycle, ensuring reliability and efficiency while managing AI-related cloud spending. This position offers an opportunity to work closely with data science teams to enhance their deployment capabilities.
Senior ML Engineer: Production ML, Observability & FinOps in Newcastle upon Tyne employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer: Production ML, Observability & FinOps in Newcastle upon Tyne
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Senior ML Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving production ML and cloud services. We want to see how you’ve tackled real-world problems, so don’t hold back!
✨Tip Number 3
Prepare for the interview like it’s the final exam! Brush up on your knowledge of REST APIs and operational backend services. We recommend practising common ML scenarios and being ready to discuss how you’d manage AI-related cloud spending.
✨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 take the initiative to connect directly with us.
We think you need these skills to ace Senior ML Engineer: Production ML, Observability & FinOps in Newcastle upon Tyne
Some tips for your application 🫡
Showcase Your Experience: When writing your application, make sure to highlight your experience with transitioning models into production. We want to see how you've tackled similar challenges in the past, so don’t hold back on those details!
Be Specific About Your Skills: Mention your proficiency in software engineering fundamentals and REST APIs clearly. We’re looking for someone who can hit the ground running, so let us know how your skills align with the role.
Demonstrate Your Cloud Knowledge: Since this role involves working in AWS, it’s crucial to mention any relevant cloud experience you have. Share examples of how you've managed AI-related cloud spending or optimised services in a cloud environment.
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 don’t miss out on any important updates during the process!
How to prepare for a job interview at hackajob
✨Know Your ML Lifecycle
Make sure you can confidently discuss the entire machine learning lifecycle. Be prepared to explain how you transition models from experimentation to production, and share specific examples of your past experiences in doing so.
✨Showcase Your Cloud Skills
Since this role involves working with AWS, brush up on your cloud knowledge. Be ready to talk about your experience with operational backend services and how you've managed AI-related cloud spending in previous roles.
✨Demonstrate Software Engineering Fundamentals
This position requires a solid understanding of software engineering principles. Prepare to discuss your proficiency in REST APIs and how you've applied these skills in real-world projects, especially in relation to ML services.
✨Collaborate with Data Science Teams
Highlight your experience working alongside data science teams. Share examples of how you've enhanced deployment capabilities and improved collaboration between engineering and data science to achieve successful outcomes.
