Machine Learning for Physical Design Intern - CPU/AI Hardware

Tenstorrent$104K — $145K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Currently pursuing a BS/MS/PhD in Electrical Engineering (EE), Electrical and Computer Engineering (ECE), Computer Engineering (CE), or Computer Science (CS)
  • Experience with algorithms, data structures, and software development in Python and C/C++
  • Deep knowledge of mathematics, probability, statistics, and algorithms
  • Experience in solving problems using Machine Learning models
  • Some knowledge of VLSI design fundamentals
  • Strong problem-solving skills
  • Exposure to synthesis, place and route, or timing analysis is a plus

Responsibilities

  • Collaborate with Physical Design engineers to develop ML-based tools for physical design
  • Extend existing machine learning systems and implement new algorithms
  • Select appropriate datasets and data representation methods for analysis
  • Conduct machine learning tests and experiments on chip design databases
  • Perform statistical analysis and fine-tune machine learning models based on test results

Benefits

  • On-site work in Santa Clara, CA or Austin, TX
  • Collaborative environment with experienced engineers
  • Focus on cutting-edge AI/ML design technologies
  • Opportunity to contribute to high-performance designs for industry-leading architectures
  • Gain experience in developing tools that impact chip implementation processes
Full Job Description
As an intern in the Physical Design (PD) team, you will work on high-performance designs going into industry leading AI/ML architectures. The student coming into this role will develop ML-based tools and flows to improve the PPA (Performance Power Area) and turnaround time for all aspects of chip implementation from synthesis to tapeout for various IPs. The work is done collaboratively with a group of highly experienced engineers across various domains of the ASIC. This role is on-site, 40 hours, based out of Santa Clara, CA or Austin, TX. Who You Are - Currently pursuing a BS/MS/PhD in EE/ECE/CE/CS. - Possessing deep knowledge of math, probability, statistics, and algorithms. - Experienced in solving problems with Machine Learning models. - Skilled in algorithms, data structures, and software development using Python and C/C++. What We Need - Ability to develop ML-based tools to improve PPA and turnaround time for chip implementation. - Work closely with other PD engineers to develop ML tools for areas such as synthesis, PnR, timing closure, and power grid analysis. - Responsibility for selecting appropriate datasets, data representation methods, and implementing new algorithms. - Capability to run machine learning tests, perform statistical analysis, and fine-tune models using test results. What You Will Learn - How to apply ML systems and flows to high-performance designs for industry-leading AI/ML architectures. - Practical experience in extending existing ML systems and implementing cutting-edge algorithms. - Gain exposure to core physical design fundamentals, including synthesis, place and route, and timing analysis. - Experience collaborating with a group of highly experienced engineers across various domains of the ASIC implementation. 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.

About Tenstorrent

Tenstorrent is a semiconductor company that designs and develops computer processors for artificial intelligence and machine learning applications. The company's processors are designed to be energy-efficient and scalable, and are used by a range of businesses, from small startups to large enterprises. Tenstorrent was founded in 2016 and is headquartered in Toronto, Ontario.
Learn more about Tenstorrent
Size
51 employees
Industry
Founded
2016

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