Machine Learning Computer Architect - Intern

Posted:
1/14/2025, 10:28:04 AM

Location(s):
Santa Clara, California, United States ⋅ California, United States

Experience Level(s):
Internship

Field(s):
AI & Machine Learning ⋅ Software Engineering

Workplace Type:
On-site

At d-Matrix, we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration.

We value humility and believe in direct communication. Our team is inclusive, and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution.  Ready to come find your playground? Together, we can help shape the endless possibilities of AI. 

Location:

Hybrid, working onsite at our Santa Clara, CA headquarters 3 days per week.

What you will do:

d-Matrix is seeking outstanding computer architects to help accelerate AI application performance at the intersection of both hardware and software, with particular focus on emerging hardware technologies (such as DIMC, D2D, PIM etc.) and emerging workloads (such as generative inference etc.). Our acceleration philosophy cuts through the system ranging from efficient tensor cores, storage, and data movements along with co-design of dataflow, and collective communication techniques. 

What you will do: 

  • As a member of the architecture team, you will contribute to features that power the next generation of inference accelerators in datacenters. 

  • This role requires to keep up the latest research in ML Architecture and Algorithms space, and collaborate with different partner teams including hardware design, compiler. 

  • Your day-to-day work will include (1) analyzing the properties of emerging machine learning algorithms and identifying functional, performance implications (2) proposing new features to enable or accelerate these algorithms, (3) studying the benefits of proposed features with performance models 

What you will bring: 

  • MS, PhD candidate in computer engineering, computer science, electrical engineering, or related field. 

  • Solid grasp in multiple of the relevant areas – computer architecture, hardware software codesign, performance modelling, ML fundamentals (particularly DNNs). 

  • Programming fluency in C/C++ or Python. 

  • Experience with developing architecture simulators for performance analysis, or hacking existing ones 

  • Research background with publication record in top-tier architecture, or machine learning venues is a huge plus (such as ISCA, MICRO, ASPLOS, HPCA, DAC, MLSys etc.) 

    #LI-DL1

Equal Opportunity Employment Policy

d-Matrix is proud to be an equal opportunity workplace and affirmative action employer. We’re committed to fostering an inclusive environment where everyone feels welcomed and empowered to do their best work. We hire the best talent for our teams, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. Our focus is on hiring teammates with humble expertise, kindness, dedication and a willingness to embrace challenges and learn together every day.

d-Matrix does not accept resumes or candidate submissions from external agencies. We appreciate the interest and effort of recruitment firms, but we kindly request that individual interested in opportunities with d-Matrix apply directly through our official channels. This approach allows us to streamline our hiring processes and maintain a consistent and fair evaluation of al applicants. Thank you for your understanding and cooperation.

d-Matrix

Website: https://www.d-matrix.ai/

Headquarter Location: Santa Clara, California, United States

Employee Count: 11-50

Year Founded: 2019

IPO Status: Private

Last Funding Type: Series B

Industries: Artificial Intelligence (AI) ⋅ Cloud Infrastructure ⋅ Data Center ⋅ Semiconductor