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- Tasks: Advance deep learning algorithms and optimise inference and compiler stack.
- Company: Leading tech company in the UK with a focus on innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Contribute to groundbreaking AI technologies and work with top engineers.
- Qualifications: MS or PhD in Computer Science, strong C/C++ or Rust skills.
- Other info: Dynamic environment with a focus on collaboration and cutting-edge projects.
The predicted salary is between 70000 - 90000 £ per year.
A leading technology company in the United Kingdom is seeking engineers to advance algorithms for deep learning and optimizations for their inference and compiler stack.
Responsibilities include:
- Developing high-performance components
- Collaborating with architects
Candidates should hold an MS or PhD in Computer Science or a related field, possess substantial experience in software engineering, and have strong skills in C/C++ or Rust.
This position offers an opportunity to contribute to cutting-edge technologies in the AI field.
Senior ML Inference & Compiler Architect in London employer: Nvidia
Contact Detail:
Nvidia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Inference & Compiler Architect in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or attend tech 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 projects, especially those related to deep learning and compiler optimisations. 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 algorithms and system design. Practice coding challenges in C/C++ or Rust, as these are crucial for the role. We recommend using platforms that focus on these skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect with us directly.
We think you need these skills to ace Senior ML Inference & Compiler Architect in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in software engineering and your skills in C/C++ or Rust. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about deep learning and how your expertise can contribute to our inference and compiler stack. Let us know what excites you about this opportunity!
Showcase Your Problem-Solving Skills: In your application, highlight specific examples where you've tackled complex problems or optimised algorithms. We love seeing how you approach challenges, especially in the context of AI technologies!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to join our innovative team!
How to prepare for a job interview at Nvidia
✨Know Your Algorithms
Make sure you brush up on the latest algorithms in deep learning and optimisations. Be ready to discuss how you've applied these in your previous roles, as well as any challenges you faced and how you overcame them.
✨Showcase Your Coding Skills
Since strong skills in C/C++ or Rust are essential, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges beforehand to boost your confidence.
✨Understand the Compiler Stack
Familiarise yourself with the inference and compiler stack relevant to the role. Be prepared to discuss how you would improve performance and what tools or techniques you would use to achieve this.
✨Collaborative Mindset
This role involves working closely with architects and other engineers. Think of examples from your past experiences where collaboration led to successful outcomes, and be ready to share these stories during the interview.