Principal System Software Engineer, AI Inference Execution

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:

Hybrid, working onsite at our Santa Clara, CA, headquarters 3 days per week.

The role: Principal System Software Engineer, AI Inference Execution

What you will do:

The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the software team, you will be responsible for the development, enhancement, and maintenance of the next-generation AI deployment software. You have had past experience working across all aspects of the full-stack toolchain and understand the nuances of what it takes to optimize and trade-off various aspects of hardware-software co-design. You are able to build and scale software deliverables in a tight development window. You will work with a team of system software experts to build out the deployment infrastructure, working closely with other software (ML and compilers) and hardware experts in the company.

What you will bring:

Minimum:

• BS in Computer Science, Engineering, Math, Physics, or related degree with 12+ years of industry software development experience and MS in Computer Science, Engineering, Math, Physics, or related degree preferred with 6+ years

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

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

• Experience with distributed, high-performance software design and implementation

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

Preferred:

• MS or PhD in Computer Science, Electrical Engineering, or related fields

• Experience with inference servers/model serving frameworks (such as TensorRT-LLM, vLLM, SGLang, etc.)

• Experience with deep learning frameworks (such as PyTorch and TensorFlow)

• Experience with deep learning runtimes (such as ONNX Runtime, TensorRT, etc.).

• Experience with distributed systems collectives such as NCCL and OpenMPI

• Experience with software testing fundamentals

• Experience deploying ML workloads (LLMs, VLMs, NLP, etc.) on distributed systems.

• Experience with Kubernetes, Ray, or other MLOps tools and techniques used from definition to deployment

• Prior startup, small team, or incubation experience

• 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.