Principal Software Engineer @ Tenstorrent

The Tenstorrent team combines technologists from different disciplines who come together with a shared passion for AI and a deep desire to build great products. We value collaboration, curiosity, and a commitment to solving hard problems. Find out more about our culture.

We are seeking an experienced Principal Software Engineer with a deep understanding of kernels and compilers to join our team. As a Principal Software Engineer, you will be responsible for leading and overseeing the design, development, and optimization of kernels and compilers for our cutting-edge software products. You will work closely with cross-functional teams, including software architects, product managers, and hardware engineers, to ensure the highest level of performance, reliability, and efficiency of our software.

Responsibilities

Develop machine learning graph compiler and kernels
Participate in the co-design of Tenstorrent’s hardware and software stack
Benchmark, analyze, and optimize performance of key machine learning applications across Tenstorrent’s hardware and software stack
Develop performance analysis and estimation infrastructure that feeds into Tenstorrent compiler
Develop high-performance run-time engine
Integrate the Tenstorrent software into leading machine learning frameworks
Work closely with machine learning engineers to discover the hardware and software requirements of current and future machine learning applications

Experience & Qualifications

BSc, MSc or PhD in Electrical/Computer Engineering or Computer Science
Experience with algorithms, data structures, and software development in C/C++. Python expertise is welcome as well
Familiarity with and passion for any of the following -- machine learning, compilers, parallel programming, high-performance and massively parallel systems, processor and computer architecture -- is a plus

Location:

Santa Clara, CA

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Responsibilities

Experience & Qualifications

6 month growth

1 year growth

2 year growth