Runtime Engineering Intern

Posted 25 Days Ago
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Sydney, New South Wales
Internship
Artificial Intelligence • Machine Learning • Software
The Role
Support development of embedded systems, implementing Linux software, and working on security and communication protocols in a multi-chip hardware architecture.
Summary Generated by Built In

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 Sydney office 3 days per week. 

The Role: Runtime Engineer Intern

What You Will Do

We are seeking an enthusiastic intern with a background in Electrical Engineering (EE) or Computer Science (CS) who is eager to work on embedded systems development, Linux software, RTOS, security and solve complex problems. We offer a range of opportunities, from Linux software implementation to low-level embedded development on the RISC-V platform, and security-related projects. Our projects are built around a complex multi-chip hardware architecture featuring PCIe 5.0, representing cutting-edge design.This position is ideal for someone with a passion for embedded technologies, whether through academic experience or personal projects. We are excited to provide training and mentorship to help you grow in the field. The ideal candidate should have a strong foundation to build on, along with a proactive attitude to learn and perform in a fast-paced, hands-on environment. 

What You will Bring:

• Must be working toward a Bachelor’s degree in Computer Science, Computer Engineering, or related

• Experience developing software in C/C++ for Linux systems or related

• Experience with Python and Bash scripting ability

• Familiarity with version control practices, ideally with git.

Preferred Qualifications

• Experience with platforms such as Raspberry Pi or RISC-V

• Experience with device driver based on Ubuntu or Zephyr

• Experience with common embedded communication protocols such as (TCP/IP, SPI, GPIO, UART, PCIe) in a real-time environment.

• Excellent verbal and written communication skills

• Ability to work effectively in a team environment

• Excellent problem-solving skills.

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.

Top Skills

Bash
C/C++
Git
Gpio
Linux
Pcie
Python
Risc-V
Rtos
Spi
Tcp/Ip
Uart
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The Company
HQ: Santa Clara, CA
102 Employees
On-site Workplace

What We Do

d-Matrix is building a new way of doing datacenter AI inferencing using in-memory computing (IMC) techniques with chiplet level scale-out interconnects. Founded in 2019, d-Matrix has attacked the physics of memory-compute integration using innovative circuit techniques, ML tools, software and algorithms; solving the memory-compute integration problem, which is the final frontier in AI compute efficiency.

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