Base Salary
$190k - $300k/yr
Responsibilities
- Develop, enhance, and maintain software kernels for ML operators on next-generation AI hardware.
- Productize the software stack for the company’s AI compute engine.
- Build SDK solutions that are intuitive for developers to use.
- Analyze and improve software performance.
- Map algorithms and AI-framework computational graphs onto modern hardware architectures.
- Navigate hardware-software co-design trade-offs and deliver scalable, high-quality software.
Requirements
- MS or PhD in computer engineering, math, physics, or a related degree.
- 5+ years of industry experience.
- Strong understanding of computer architecture, data structures, system software, and machine-learning fundamentals.
- Proficiency in C/C++ and Python development in a Linux environment using standard development tools.
- Experience implementing algorithms in C/C++ and Python.
- Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, and AI accelerators using libraries such as CUDA.
- Experience implementing ML operators including GEMMs, convolutions, softmax, layer normalization, and pooling.
- Prior startup, small-team, or incubation experience is preferred.
- Experience with TensorFlow, PyTorch, ML compilers such as MLIR, LLVM, TVM, or Glow, and deep-learning models for computer vision, NLP, or recommendation is preferred.
- Experience developing for embedded SIMD vector processors such as Tensilica, or working at a cloud provider or AI compute/subsystem company, is preferred.
Benefits
- Santa Clara, California headquarters or regional office location; remote work is possible.
About d-Matrix
d-Matrix is an AI infrastructure company building the next generation of inference computing for the era of generative and agentic AI. Founded in 2019, d-Matrix is rethinking AI inference from the ground up with a full-stack approach spanning silicon, systems, networking, and software. Its flagship products, including the Corsair™ inference platform and JetStream™ inference fabric, are purpose-built to deliver high-performance, low-latency, and energy-efficient AI inference at datacenter scale. The company has raised nearly $500 million from a global syndicate of leading venture capital firms, sovereign wealth funds, and strategic investors, including Playground Global, Bullhound Capital, M12 (Microsoft’s Venture Fund), SK hynix, Temasek, Qatar Investment Authority, and Singapore’s EDBI. The company’s most recent financing valued d-Matrix at approximately $2 billion. As AI shifts from training to inference, the demands on AI infrastructure are changing. d-Matrix is building the infrastructure required to power the next generation of real-time AI at scale.