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Staff Software Engineer, SIMD Kernels

D Matrix

Santa Clara, CA · $190k–$300k a year · Posted July 28, 2026

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  • Python
  • Machine learning
  • Linux
  • C#
  • Pytorch

About the job

Join d-Matrix and help build the future of AI inference. We’ve pioneered a memory-centric architecture that brings compute directly into memory, making AI faster, more energy efficient, and accessible on a global scale. From chips and software to rack-scale systems, our team is tackling some of AI infrastructure’s hardest challenges — and shipping breakthrough technology today. If you want to create what comes next and help make infinite inference possible, we’d love to hear from you.

Our culture is built on respect, collaboration, and direct communication. We value humility, we believe our different perspectives lead to better solutions, and we’re looking for people who are driven by execution and energized by hard problems.

Location:

Santa Clara, CA headquarters, or any of our regional offices. Will consider remote.

The Role: Staff Software Engineer, SIMD Kernels

What you will do:

As a member of the SIMD Kernels team, you will help productize the software stack for our AI compute engine. You will develop, enhance, and maintain software kernels for ML operators—such as softmax, layer norm, and activation functions—for next‑generation AI hardware. You will also build solutions that make our SDK intuitive for developers to use and analyze performance.

You have experience building software kernels for modern hardware architectures and understand how to map algorithms and AI‑framework computational graphs onto those architectures. You’re comfortable working across the full toolchain and navigating hardware–software co‑design trade‑offs. You can deliver and scale high‑quality software quickly in a fast‑moving development environment.

What you will bring:

Minimum:

- MS or PhD in computer engineering, math, physics, or a related degree with 5+ years of industry experience.

- Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.

- Proficient in C/C++ and Python development in Linux environment and using standard development tools.

- Experience in implementing algorithms in C/C++ and Python.

- Experience in implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, AI accelerators using libraries such as CUDA, etc.

- Experience in implementing operators commonly used in ML workloads—GEMMs, Convolutions, softmax, layer normalization, pooling, etc.

- Self-motivated team player with a strong sense of ownership and leadership.

Preferred:

- Prior startup, small team, or incubation experience.

- Experience with ML frameworks such as TensorFlow and/or PyTorch.

- Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc.

- Experience with a deep learning framework (such as PyTorch or TensorFlow) and ML models for CV, NLP, or recommendation.

- Experiences in development for embedded SIMD vector processors such as Tensilica.

- Work experience at a cloud provider or AI compute/subsystem company.

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 individuals 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 all applicants. Thank you for your understanding and cooperation.