Acceleration Kernel Developer

As an Acceleration Kernel Developer at Tenstorrent, your responsibilities include designing, developing, and maintaining kernel-level software components tailored for machine learning applications. You'll optimize low-level workloads, implement tensor compute optimizations, and collaborate closely with machine learning engineers. Performance profiling, testing, and debugging will also be an essential part of your role, ensuring that our software achieves peak efficiency.

To qualify for the Acceleration Kernel Developer role at Tenstorrent, candidates should have a Bachelor's degree in Computer Science, Computer Engineering, or a related field. Proven experience in kernel development with a focus on low-level optimizations is essential, alongside proficiency in C/C++. Familiarity with machine learning frameworks, strong problem-solving skills, and comfort working in a Linux environment are also preferred.

The hybrid work model at Tenstorrent allows Acceleration Kernel Developers to enjoy the flexibility of working both in the office and remotely. This approach fosters a balanced working environment, enabling better collaboration with team members while also providing the ability to focus on complex development tasks in a comfortable setting. It supports creativity and innovation, which are key in the fast-paced AI sector.

An Acceleration Kernel Developer at Tenstorrent should be proficient in programming languages such as C and C++. These languages are critical for developing kernel-level software and performing low-level optimizations. Additionally, familiarity with GPU programming languages such as CUDA or OpenCL is considered a plus, allowing for more effective handling of tensor optimization tasks.

At Tenstorrent, Acceleration Kernel Developers can expect a collaborative and dynamic team environment. The company encourages open communication, curiosity, and teamwork. You will work alongside an elite group of engineers who are dedicated to solving complex problems in AI technology, making contributions that lead to valuable innovations in the field.

When discussing your experience with kernel development, focus on specific projects where you were involved in the design and implementation of kernel-level software. Highlight any optimizations you made, especially in terms of performance for machine learning or high-performance computing applications, and how your contributions impacted those projects.

In your response, detail specific optimization techniques you are familiar with, such as loop unrolling, memory access optimization, and utilizing specific CPU instructions. Provide examples of how you applied these techniques in real-world scenarios, particularly in improving performance and reducing resource usage.

Discuss your methodology for performance profiling, emphasizing tools you've used such as gprof, valgrind, or specific profiling tools for GPU programming. Explain how you identify bottlenecks and the steps you take to address them, including any testing frameworks you incorporate into your optimization workflow.

Share your strategies for keeping current, whether through online courses, attending conferences, or participating in relevant webinars. Mention any specific resources such as journals or websites dedicated to AI and kernel development that you regularly follow, demonstrating your commitment to continuous learning.

In your answer, provide details about your previous collaborations with machine learning engineers and data scientists. Discuss how you integrated kernel optimizations within their frameworks and any challenges you faced during these collaborations. Highlight the importance of communication and teamwork in achieving shared objectives.

Emphasize the importance of clear documentation as a part of the development lifecycle. Describe how you create documentation for your code, APIs, and best practices and how this aids collaboration within the team. You could also discuss instances where documentation helped in troubleshooting or onboarding new team members.

Be prepared to explain a specific challenging bug in detail. Discuss your thought process during the troubleshooting phase, the tools you used to identify the issue, and the resolution steps you took. Highlighting how you remained calm under pressure during this problem-solving process will show your resilience and technical skills.

Reflect on what excites you about Tenstorrent’s mission and culture. Mention its commitment to addressing complex problems in AI and its innovative approach to technology development. You could also express an eagerness to contribute to their high-performance systems and collaborate with a team of skilled professionals.

Discuss your approach to task prioritization, emphasizing your ability to balance quality and deadlines. Talk about how you assess project requirements, communicate with stakeholders, and determine which tasks offer the greatest impact. Time management techniques and tools you use could also be valuable here.

In your answer, discuss any hands-on experience you have with GPU programming, particularly focusing on how it enhances kernel optimizations. Share projects where GPU programming played a significant role and how your experience has equipped you to contribute to kernel-level developments at Tenstorrent.