Engineering Intern jobs in United Arab Emirates

Overview:

d-Matrix has fundamentally changed the physics of memory-compute integration with our digital in-memory compute (DIMC) engine. The holy grail of AI compute has been to break through the memory wall to minimize data movements. We've achieved this with a first-of-its-kind DIMC engine. Having secured over $154M, $110M in our Series B offering, 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. We are poised to meet the energy and performance demands of these Large Language Models.

The company has 100+ employees across Silicon Valley, Sydney, and Bengaluru. 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.

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

The Role:

The Software Team at d-Matrix is looking for an ML Software Engineering Intern to join the team. Location can be Santa Clara / remote. You will be joining a team of exceptional professionals enthusiastic about tackling some of the biggest challenges of AI compute. In this role, you will work on either or multiple of the following domains: (1) develop performant implementations of SOTA ML models such as LLaMA, GPT, BERT, DLRM, etc. (2) develop and maintain tools for performance simulation, analysis, debugging, profiling. (3) develop AI infra software such as kernel compiler, inference engine, model factory, etc. (4) develop QA systems/automation software. You will engage and collaborate with the rest of the SW team to meet development milestones and contribute to the publication of papers and intellectual properties as applicable.

Minimum Requirements:

• Enrolled in a Bachelor's degree in Computer Science, Electrical and Computer Engineering, or a related scientific discipline.
• A problem solver, able to break down and simplify complex problems to come up with elegant and efficient solutions.
• Proficient in programming with either Python/C/C++ programming languages.

Desired Qualifications:

• Enrolled in either a MS or PhD in Computer Science, Electrical and Computer Engineering, or a related scientific discipline.
• Understanding of CPU/GPU architectures and their memory systems.
• Experience with specialized HW accelerators for deep neural networks.
• Experience developing high performance kernels, simulators, debuggers, etc., targeting GPUs/Other accelerators.
• Experience using Machine Learning frameworks, like PyTorch (preferred), Tensorflow, etc.
• Experience with Machine Learning compilers, like MLIR (preferred), TVM, etc.
• Experience deploying inference pipelines and using or developing inference engines such as vLLM, TensorRT-LLM.
• Passionate about AI and thriving in a fast-paced and dynamic startup culture.

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.