Micro-Architect / RTL Design - CPU, Principal

Reposted 4 Days Ago
Be an Early Applicant
Santa Clara, CA
In-Office
196K-300K Annually
Senior level
Artificial Intelligence • Machine Learning • Software
The Role
Design and develop micro-architecture and RTL for AI Control subsystems, focusing on performance, efficiency, and verification. Engage in silicon validation.
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 Santa Clara, Ca headquarters 3-5 days per week.

Micro-Architect / RTL Design - CPU, Principal

What You Will Do:

• Responsible for the micro-architecture and design of the AI Control sub-system modules including Hardware Execution Engines.

• Own design, document, execute and deliver fully verified, high performance, area, and power efficient RTL to achieve the design targets and specifications

• Design of micro-architecture and RTL, synthesis, logic and timing verification using leading edge CAD tools and semiconductor process technologies

• Design and Implement logic functions that enable efficient test and debug

• Participate in silicon bring-up and validation for blocks owned

What You Will Bring:

• Master’s degree in electrical engineering, Computer Engineering or Computer Science with 5 years of meaningful work experience

• Experience in micro-architecture and RTL development (Verilog/System Verilog), focused on Processor and sub-system design, Digital Signal Processing blocks.

• Exposure to Computer Architecture & Arithmetic is required. Experience with RISC-V/Tensilica/ARM/Mips processors is required

• Exposure to Computer Architecture & Arithmetic is required. Experience with Floating point and Integer Arithmetic and Numerics is a plus. Exposure to Interconnect and Bus Interfaces is required.

• Good understanding of ASIC design flow including RTL design, verification, logic synthesis and timing analysis

• Strong interpersonal skills and an excellent teammate

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

Arm
Mips
Risc-V
System Verilog
Tensilica
Verilog
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The Company
HQ: Santa Clara, CA
102 Employees

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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