Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design efficient GPU communication kernels and develop frameworks for deep learning models.
- Company: Dynamic tech company focused on next-generation AI/ML technology.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Join a high-impact team and work with cutting-edge AI/ML technologies.
- Qualifications: Proficient in C++ and Python, with GPU programming experience.
- Other info: Exciting environment with opportunities to innovate and grow your career.
The predicted salary is between 36000 - 60000 £ per year.
A dynamic tech company is seeking a talented ML Systems/Infrastructure Engineer to optimize its AI/ML software with advanced network hardware.
Responsibilities include:
- Designing efficient GPU communication kernels
- Developing distributed frameworks for deep learning models
- Debugging GPU applications
Candidates should be proficient in C++ and Python, with hands-on experience in GPU programming and communication libraries. This role offers a chance to contribute to a crucial, high-impact team focused on next-generation technology.
ML Systems Engineer: GPU & Distributed Infra in London employer: Oriole
Contact Detail:
Oriole Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Systems Engineer: GPU & Distributed Infra in London
✨Tip Number 1
Network, network, network! Reach out to folks in the industry, especially those working with GPU and distributed systems. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in C++ and Python, especially any work related to GPU programming. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of communication libraries and deep learning frameworks. Practice coding challenges that focus on optimising algorithms and debugging GPU applications.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact in AI/ML. Your next big opportunity could be just a click away!
We think you need these skills to ace ML Systems Engineer: GPU & Distributed Infra in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your proficiency in C++ and Python right from the start. We want to see your hands-on experience with GPU programming and communication libraries, so don’t hold back on showcasing those projects!
Tailor Your Application: Take a moment to customise your application for this role. Mention specific experiences that relate to designing GPU communication kernels or developing distributed frameworks. This shows us you’re genuinely interested in the position.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that are easy to read. Use bullet points if necessary to make your achievements stand out!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Oriole
✨Know Your Tech Inside Out
Make sure you’re well-versed in C++ and Python, as these are key for the role. Brush up on GPU programming and communication libraries, and be ready to discuss your hands-on experience with specific examples.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some technical challenges during the interview. Think about past projects where you optimised AI/ML software or developed distributed frameworks, and be ready to explain your thought process and solutions.
✨Understand the Company’s Vision
Research the company’s focus on next-generation technology. Be prepared to discuss how your skills can contribute to their goals, especially in optimising GPU communication kernels and debugging applications.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the team and projects. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
