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- Tasks: Design and maintain machine learning tooling in Python while supporting research teams.
- Company: Join a leading technology recruitment agency in Cambridge, UK.
- Benefits: 12-month contract with competitive pay and the chance to work on cutting-edge AI projects.
- Why this job: Collaborate with world-class researchers and enhance your skills in machine learning.
- Qualifications: 4+ years of experience in Python and machine learning systems, familiar with PyTorch or TensorFlow.
- Other info: Unique opportunity to contribute to advanced AI capabilities in a dynamic environment.
The predicted salary is between 42000 - 84000 £ per year.
A technology recruitment agency is seeking a Software Engineer/Developer (ML Infrastructure) for a 12-month contract in Cambridge, UK. The role involves designing and maintaining machine learning tooling in Python, supporting research teams, and improving infrastructure systems.
Ideal candidates will possess 4+ years of experience with a strong focus on Python and machine learning systems, along with familiarity with PyTorch or TensorFlow. This is a unique opportunity to work with world-class researchers and contribute to advanced AI capabilities.
ML Infrastructure Engineer — Python & ML Pipelines in Cambridge employer: Harvey Nash
Contact Detail:
Harvey Nash Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Infrastructure Engineer — Python & ML Pipelines in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working with ML infrastructure. A friendly chat can lead to insider info on job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects and any machine learning pipelines you've built. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML knowledge. Practice coding challenges and be ready to discuss your past projects in detail. We want you to shine!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace ML Infrastructure Engineer — Python & ML Pipelines in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and machine learning systems. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or tools you've worked with!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about ML infrastructure and how you can contribute to our team. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Technical Skills: Don’t forget to mention your familiarity with PyTorch or TensorFlow in your application. We’re looking for candidates who can hit the ground running, so let us know how you’ve used these tools in your previous work.
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 unique opportunity to work with world-class researchers!
How to prepare for a job interview at Harvey Nash
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python in detail, including any specific libraries or frameworks you've used, especially in relation to machine learning.
✨Familiarise Yourself with ML Tools
Since the role involves working with ML pipelines, it’s crucial to have a solid understanding of tools like PyTorch and TensorFlow. Prepare to talk about projects where you've implemented these technologies and how they contributed to the success of your work.
✨Showcase Your Problem-Solving Skills
Be prepared to tackle some technical questions or case studies during the interview. Think about how you can demonstrate your problem-solving abilities, particularly in designing and maintaining ML infrastructure.
✨Research the Company and Its Projects
Take some time to learn about the company and their current research projects. This will not only help you understand their goals but also allow you to ask insightful questions, showing your genuine interest in contributing to their advanced AI capabilities.
