Software Intern - AI Compilers at Tenstorrent

Austin, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

02 Feb, 26

Salary

70.0

Posted On

04 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Compilers, Parallel Programming, High-Performance Systems, Processor Architecture, Computer Architecture, Algorithms, Data Structures, Software Development, C++, Python, Performance Analysis, Optimization, Digital Design, Verification, Firmware

Industry

Computer Hardware Manufacturing

Description

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. At Tenstorrent, you will have the chance to accelerate your career by working on challenging engineering problems with a dedicated mentor and the opportunity to move between the digital design, verification, firmware, software and system engineering teams. This role is hybrid based in Austin, TX Responsibilities: Develop machine learning graph compiler 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 Develop novel ML models and primitives that take advantage of Tenstorrent’s breakthrough architecture to deliver orders of magnitude performance & efficiency improvements Experience & Qualifications: Final year BS/MS or PhD candidate in EE/ECE/CE/CS with a strong GPA 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 Strong problem solving and analytical skills Compensation for all interns at Tenstorrent ranges from $50/hr - $70/hr including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

Responsibilities

Develop machine learning graph compiler and 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.