Backed by Lux.
About the role
Backed by top-tier investors and led by industry veterans, we’re scaling rapidly. We seek forward-thinking engineers and operators who thrive in a collaborative environment and excel at solving complex challenges from first principles. If you want to build infrastructure that fundamentally changes what the world can accomplish with AI, come join us! Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor’s or Master’s in Electrical Engineering, Computer Engineering, or related field
- 10+ years of experience in SoC or compute architecture, with a focus on AI acceleration or high-performance compute
- Deep understanding of RISC-V architecture, vector extensions, and parallel compute design
- Experience with multi-core cluster integration, shared memory hierarchies, and cache coherency protocols
- Familiarity with matrix multiplication engines, SIMD/vector processors, and AI kernel optimization
- Strong background in embedded systems architecture, system-level performance modeling, and debug methodologies
More about this role
We’re a fast-moving, US-Israeli AI startup building next-generation infrastructure for the world’s most demanding AI workloads. Our mission is to accelerate the future of intelligence and make it ubiquitously accessible by delivering full stack custom AI servers optimized for large-scale inference and training.
Backed by top-tier investors and led by industry veterans, we’re scaling rapidly. We seek forward-thinking engineers and operators who thrive in a collaborative environment and excel at solving complex challenges from first principles. If you want to build infrastructure that fundamentally changes what the world can accomplish with AI, come join us!
We are seeking an experienced SoC Architect - AI Acceleration (RISC-V and Compute Cluster Development) to lead the architecture and integration of Majestic’s compute subsystem.
In this role, you will define and optimize the RISC-V-based compute clusters, vector engines, and shared memory structures that power high-performance AI workloads.
You’ll collaborate closely with design, verification, compiler, and ML software teams to define architectures that maximize performance per watt while ensuring scalability across multiple...
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