Staff AI IP Performance Engineer

As a Staff AI IP Performance Engineer at Tenstorrent, your main responsibilities include leading performance and power measurement activities, developing competitive benchmarking models, and collaborating with various cross-functional teams to drive architectural innovations. You will also explore optimizations at various levels and support pre-sales evaluations using performance models to demonstrate the value of our AI IP products.

To apply for the Staff AI IP Performance Engineer position at Tenstorrent, candidates should have a Master’s or PhD in Computer Science, Electrical Engineering, or a related field. Additionally, a solid foundation in computer architecture, programming proficiency in Python or C/C++, and at least 3 to 7 years of relevant experience in performance measurement, benchmarking, and system architecture is required.

Tenstorrent complies with U.S. export control laws by requiring documentation and information related to citizenship and residency status, as employment may provide direct access to systems and technologies that are regulated. Candidates selected for the Staff AI IP Performance Engineer position must provide necessary documentation to ensure compliance with these regulations before employment begins.

Success in the Staff AI IP Performance Engineer role at Tenstorrent demands exceptional problem-solving abilities, strong analytical skills, and a passion for AI technologies. Additionally, proficiency in programming languages like Python or C/C++ and the capability to build models using frameworks like SystemC will greatly enhance your performance in this position.

While Tenstorrent welcomes candidates of various experience levels for the Staff AI IP Performance Engineer position, it is essential to have at least 3 years of relevant experience or an appropriate educational background. Candidates with foundational knowledge in AI and deep learning principles are strongly encouraged to apply, as the position is designed for skilled individuals looking to further their careers in a cutting-edge environment.

When answering this question, highlight specific projects you've worked on that involved performance measurement. Discuss your methodologies and how they contributed to understanding AI technologies, especially in terms of optimizing performance in deep learning models. Provide concrete examples to showcase your technical expertise.

Demonstrate your knowledge of generative models by defining them and discussing their applications in AI. Share insights on how these models operate, particularly in training and inference, and relate this understanding back to enhancing performance in IP products at Tenstorrent.

Emphasize your communication skills and how you've successfully collaborated with different teams in past roles. Provide examples of projects where you incorporated feedback and drove results through teamwork, highlighting your adaptability in various environments.

Here, your answer should focus on a specific challenge in system architecture you faced, outlining the steps taken to analyze and solve the problem. Discuss the impact of your solution on the project or product, demonstrating your analytical and problem-solving skills.

Be specific about the languages you are comfortable with, especially Python and C/C++. Discuss how you have used them in past projects, particularly in building simulators or performance models, which will illustrate your hands-on experience and technical capabilities for the role.

Discuss methods you use for benchmarking, such as defining metrics, developing test scenarios, and interpreting results. Mention how you analyze these benchmarks to derive insights that contribute to design improvements in AI products at Tenstorrent.

Describe your approach to continuous learning in the fast-paced AI landscape. This could include attending seminars, engaging with relevant literature, participating in online communities, or pursuing further education, thus showcasing your commitment to professional development.

Explain the importance of energy efficiency in AI IP products, particularly in terms of performance and cost-effectiveness. Mention specific metrics or standards in energy measurement and how these influence design decisions in your experience.

Your answer should illustrate your ability to simplify complex information. Provide an example of when you communicated technical aspects effectively to a non-technical audience, showcasing your interpersonal skills while maintaining technical accuracy.

Reflect on Tenstorrent’s vision for AI technology and how your personal interests align with their mission. Discuss aspects such as working at the cutting edge of technology, being part of a collaborative team, or contributing to significant innovations that shape the industry.