Tech Lead, GPU Kernel Engineer - job 1 of 2

As a Tech Lead, GPU Kernel Engineer at Wayve, your primary responsibilities include leading a multi-disciplinary team of GPU kernel engineers, managing the strategic direction of GPU kernel development, and ensuring efficient model deployment on autonomous vehicles. You will break down large milestones into manageable objectives, work closely with ML and Software teams, and focus on developing hands-on GPU kernel solutions while optimizing models for performance.

To qualify for the Tech Lead, GPU Kernel Engineer position at Wayve, candidates should have proven experience as a technical lead or senior engineer on complex engineering projects. A strong background in developing GPU kernels (CUDA, OpenCL), proficiency in C++, and familiarity with ML frameworks like PyTorch are essential. Excellent communication skills and the ability to mentor a team are also key requirements.

At Wayve, the hybrid working model allows Tech Lead, GPU Kernel Engineers to balance office time with remote work. You can determine a schedule that fits best for you and your team, ensuring collaboration and innovation during core hours while still enjoying the flexibility of working from home. This setup promotes a healthy work-life balance while fueling creativity.

As a Tech Lead, GPU Kernel Engineer at Wayve, expect to engage in high-impact, early-stage projects aimed at deploying transformative AI models in autonomous vehicles. This includes developing and optimizing GPU kernels for efficient inference on multiple hardware accelerators, thus playing a crucial role in enhancing the usability and safety of automated driving systems.

Wayve fosters a diverse, inclusive, and innovative culture where every employee's contributions matter. As a Tech Lead, GPU Kernel Engineer, you’ll be a part of an environment that values unique perspectives, encourages learning, and supports collaboration, ensuring that you feel valued and respected in your role.

When answering this question, focus on specific projects where you successfully developed GPU kernels. Mention the tools and technologies you used, such as CUDA or OpenCL, and highlight how your work contributed to the overall success of the project. Including metrics or outcomes can make your response more impactful.

Discuss your leadership style and how it fosters collaboration and communication within your team. You might share specific examples of how you break down complex projects into actionable goals, facilitate team discussions, or mentor junior engineers. Highlighting your ability to adapt to different situations will also showcase your leadership effectiveness.

Outline your approach to model optimization, including techniques like pruning, quantization, and efficient data management. Mention specific frameworks you are familiar with, such as PyTorch, and discuss any experience you have with performance benchmarking to ensure your models run efficiently on target hardware.

Share specific challenges you've encountered, such as hardware constraints or integration issues, and explain how you addressed them. Emphasize your problem-solving skills and how your actions contributed to successful project outcomes.

Discuss your experience with C++, focusing on how you've applied it in GPU programming. Share examples of applications or projects where your C++ skills made a significant impact and highlight your understanding of advanced language features versus challenges in GPU programming.

Talk about a specific instance where you identified a conflict, how you approached the parties involved, and the steps you took to mediate the situation. Demonstrate your communication and interpersonal skills, stressing the positive outcome of your conflict resolution efforts.

Express your passion for the field of autonomous technology and how Wayve's innovative approach aligns with your personal career goals. Highlight specific aspects of the company's mission and technologies that inspire you and discuss how you see your skills contributing to their success.

Detail your strategies for continuous learning, such as following industry news, participating in conferences, or engaging with professional networks. Mention specific sources of information or learning resources that you find particularly valuable in keeping your skills current.

Emphasize the importance of collaboration in your work. Provide examples of how you have fostered teamwork in past projects, whether through regular meetings, shared resources, or collaborative coding environments. Illustrating your experience with cross-functional teams will strengthen your answer.

Share a specific innovation or improvement you made that had a measurable impact on project outcomes or team efficiency. Discuss the problem you identified, the solution you proposed, how you implemented it, and the positive results that followed.