Software Architect for AI Compute Engine
4 weeks ago
d-Matrix is revolutionizing the field of memory-compute integration with our cutting-edge digital in-memory compute (DIMC) engine. This innovative technology has the potential to break through the memory wall, minimizing data movements and paving the way for significant advancements in AI compute.
We are seeking a highly skilled Software Architect to join our team and help productize the SW stack for our AI compute engine. As part of our Software team, you will be responsible for the development, enhancement, and maintenance of the development and testing infrastructure for next-generation AI hardware.
The ideal candidate will have a strong grasp of computer architecture, data structures, system software, and machine learning fundamentals. Proficiency in Python/C/C++ development in a Linux environment and experience with deep learning frameworks (such as PyTorch, Tensorflow) are also essential. Additionally, a research background with a publication record in top-tier ML/Computer architecture conferences is highly desirable.
Responsibilities include:
- Implementing and optimizing ML workloads and low-level software algorithms for specialized hardware such as FPGAs, DSPs, DL accelerators.
- Experience with ML Models from definition to deployment including training, quantization, sparsity, model preprocessing, and deployment.
- Work experience at a cloud provider or AI compute / sub-system company.
What We Offer:
We are 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.
d-Matrix is poised to advance Large Language Models to scale Generative inference acceleration with our chiplets and In-Memory compute approach. We are on track to deliver our first commercial product in 2024 and are poised to meet the energy and performance demands of these Large Language Models. Our pedigree comes from companies like Microsoft, Broadcom, Inphi, Intel, Texas Instruments, Lucent, MIPS, and Wave Computing. Our past successes include building chips for all the cloud hyperscalers globally - Amazon, Facebook, Google, Microsoft, Alibaba, Tencent, along with enterprise and mobile operators like China Mobile, Cisco, Nokia, Ciena, Reliance Jio, Verizon, AT&T.
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