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- Tasks: Design and develop cutting-edge GPGPU software, optimizing performance for AI and HPC applications.
- Company: Join a leading brand in Graphics/GPU development based in Central London!
- Benefits: Work in a dynamic environment with opportunities for growth and innovation.
- Why this job: Be at the forefront of technology, shaping the future of GPU development and AI applications.
- Qualifications: Bachelor's degree in computer science or related field with 5+ years of experience required.
- Other info: Hands-on experience with C/C++ and GPGPU APIs like CUDA/HIP/OpenCL is essential.
The predicted salary is between 43200 - 72000 £ per year.
Job Description We are working with one of the upcoming brands in Graphics/GPU development who are looking to add to their team in Central London! Job Description: 1.Designing and developing GPGPU software stack, including Runtime and Driver. 2.Implementing new GPGPU driver features based on AI and HPC application requirements. 3.Implementing GPGPU software support for new GPGPU hardware features. 4.Profiling performance bottlenecks and conducting performance optimization for key applications. To excel in this role, candidates must possess the following qualifications: 1.A bachelor’s degree in computer science, computer engineering, or a related field, with a minimum of 5 years of industry experience. 2.Excellent development and debugging skills with hands-on proficiency in C/C++. 3.Working experience in GPU or GPGPU UMD driver development. 4.Proficiency and working experience with GPGPU APIs such as CUDA/HIP/OpenCL. Preferred Qualifications: 5.Familiarity with CUDA or ROCm development and debugging. 6.Good understanding of GPU hardware/software architecture, including familiarity with 3D rendering pipeline or computer pipeline. …
GPGPU Software Engineer employer: Microtech Global Ltd
Contact Detail:
Microtech Global Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GPGPU Software Engineer
✨Tip Number 1
Make sure to showcase your hands-on experience with C/C++ in your conversations. Highlight specific projects where you developed or debugged GPGPU software, as this will resonate well with the team.
✨Tip Number 2
Familiarize yourself with the latest trends in AI and HPC applications. Being able to discuss how these technologies impact GPGPU development can set you apart during interviews.
✨Tip Number 3
Prepare to discuss your experience with GPGPU APIs like CUDA, HIP, or OpenCL. Having concrete examples of how you've implemented features or optimized performance will demonstrate your expertise.
✨Tip Number 4
Research the company’s recent projects and innovations in GPU development. Showing that you are informed about their work and can contribute ideas will make a strong impression.
We think you need these skills to ace GPGPU Software Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in GPGPU software development, particularly your proficiency in C/C++ and any relevant projects you've worked on. Emphasize your hands-on experience with GPGPU APIs like CUDA, HIP, or OpenCL.
Craft a Strong Cover Letter: In your cover letter, express your passion for GPU technology and how your background aligns with the job requirements. Mention specific projects or achievements that demonstrate your skills in performance optimization and driver development.
Showcase Relevant Experience: When detailing your work experience, focus on roles where you designed or developed GPGPU software stacks or implemented new driver features. Use metrics to quantify your impact, such as performance improvements or successful project completions.
Highlight Continuous Learning: Mention any recent courses, certifications, or personal projects related to GPGPU development or AI applications. This shows your commitment to staying updated in a rapidly evolving field.
How to prepare for a job interview at Microtech Global Ltd
✨Showcase Your Technical Skills
Be prepared to discuss your experience with C/C++ and GPGPU APIs like CUDA, HIP, or OpenCL. Bring examples of projects where you've implemented driver features or optimized performance, as this will demonstrate your hands-on proficiency.
✨Understand the Company’s Focus
Research the company’s recent developments in GPU technology and their specific applications in AI and HPC. This knowledge will help you tailor your responses and show that you're genuinely interested in their work.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your debugging skills and ability to profile performance bottlenecks. Practice explaining your thought process clearly, as this will highlight your analytical skills and problem-solving approach.
✨Discuss Your Experience with Hardware Architecture
Since understanding GPU hardware/software architecture is crucial, be ready to talk about your familiarity with the 3D rendering pipeline or computer pipeline. Relate your past experiences to how they can benefit the team’s goals.
