Infrastructure Developer, Kernel Development

An Infrastructure Developer position at Tenstorrent involves creating tools to automate the testing of ML acceleration kernels and models, analyzing performance data, and ensuring quality and performance improvements. You'll be working closely with the DevOps team to integrate testing needs into CI/CD pipelines while developing innovative solutions that enhance engineering productivity.

For the Infrastructure Developer role at Tenstorrent, candidates should have a BSc or advanced degree in fields like Computer Engineering, Computer Science, or Software Engineering. Additionally, 2+ years of hands-on experience in software development or software test engineering is essential, along with proficiency in Python, Linux scripting, and an understanding of cloud infrastructure.

Successful candidates for the Infrastructure Developer role at Tenstorrent should excel in Python development, have experience with databases and cloud tools, and possess excellent collaboration skills. Understanding machine learning models and efficiency in using tools like Docker and GitHub pipelines will be advantageous in this position.

Tenstorrent fosters a collaborative, innovative, and fast-paced work environment where Infrastructure Developers are encouraged to think outside the box. With a hybrid working model based in Toronto, you’ll have access to a diverse team that shares a passion for excellence in AI technology.

The application process for the Infrastructure Developer position at Tenstorrent includes an initial resume review followed by interviews tailored to assess your fit for the team and the technical aspects of the role. Candidates at various experience levels are welcome; offers will depend on the specific qualifications and expertise of each applicant.

When answering this question, focus on specific projects where you've used Python to build or enhance testing frameworks. Highlight your problem-solving skills and any tools or libraries you utilized, such as Pytest or unittest, and explain how your contributions improved the testing process.

Discuss your familiarity with CI/CD tools and how you've successfully integrated automated testing in past projects. Be ready to mention any specific processes or results you've achieved, and emphasize the importance of continuous feedback and quick issue resolution.

Share a specific challenge, such as integrating new tools into existing workflows or improving test coverage. Explain how you tackled the issue, the strategies you used, and what the outcome was. Focus on your adaptability and willingness to learn from experiences.

When discussing features, select one that relates to performance improvement in ML models or testing frameworks. Explain the feature, the metrics you targeted, and detail how you measured the success of that implementation. Include both quantitative and qualitative benefits.

Outline your communication strategy, emphasizing collaboration tools and practices you use to keep all stakeholders informed. Share examples of successful collaboration, the importance of clarity in documentation, and how you resolve misunderstandings if they arise.

Discuss how you utilize data analysis to inform your testing approach. Mention the tools you use for data visualization and any techniques that help you interpret results, thereby driving improvements in both testing and performance criteria.

Explain your time management techniques, such as using agile methodologies or prioritization frameworks like the Eisenhower Matrix. Give examples of how you balance competing priorities while ensuring quality and efficiency.

Share a specific project that exemplifies your commitment to continuous improvement, detailing the steps you took to assess and enhance processes. Highlight how you engaged with team members and any measurable results that followed from your initiatives.

Talk about specific visualization tools such as Superset or Tableau that you've worked with. Describe how you implement data insights into actionable reporting and how these dashboards added value to project outcomes.

Discuss your proactive approach to learning, whether through online courses, attending workshops, or self-study. Emphasize your enthusiasm for staying current with the latest technologies in software infrastructure and automation.