Senior Staff AI System Software Engineer

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 days per week. The role: Senior Staff AI/ML System Software Engineer 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 compiler experts to build out the compiler infrastructure, working closely with other software (ML, systems) and hardware (mixed signal, DSP, CPU) experts in the company. What you will bring: Minimum: - BS in Computer Science, Engineering, Math, Physics or related degree with 7+ years of industry software development experience and MS in Computer Science, Engineering, Math, Physics or related degree preferred with 5 + years - Strong grasp of computer architecture, data structures, system software, 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. - Prior startup, small team, or incubation experience.  - Work experience at a cloud provider or AI compute/subsystem company. - Experience implementing SIMD algorithms on vector processors.  - Experience with open-source ML compiler frameworks such as MLIR. - Experience with deep learning frameworks (such as PyTorch and TensorFlow). - Experience with deep learning runtimes (such as ONNX Runtime, TensorRT, ...). - Experience with inference servers/model serving frameworks (such as Triton, TFServ, KubeFlow, …). - Experience with distributed systems collectives such as NCCL and OpenMPI. - Experience deploying ML workloads on distributed systems in a multitenancy environment. - Experience with MLOps from definition to deployment, including training, quantization, sparsity, model preprocessing, and deployment. - Experience training, tuning, and deploying ML models for CV (ResNet), NLP (BERT, GPT), and/or recommendation systems (DLRM). 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.