Machine Learning Research Intern

Role overview

Join d-Matrix as a Machine Learning Research Intern in a 12-week remote/hybrid program. You’ll work with researchers and engineers to develop and evaluate state-of-the-art deep learning techniques, including collaboration with academic labs and contributions to publications and intellectual property.

Key missions

• Design, implement, and evaluate efficient deep neural network architectures and algorithms for d-Matrix’s AI compute engine.
• Collaborate with internal ML researchers and the Software team to meet R&D and stack development milestones.
• Conduct research to inform hardware design.
• Develop and maintain tools for high-level simulation and research.

Requirements

• Hands-on experience with modern neural network architectures, including MoEs (Mixture of Experts) and Diffusion models.
• Strong current knowledge of machine learning and deep learning.
• Prefer efficient deep learning experience: quantization, sparsity, distillation.
• Pursuing a Master’s/PhD in a relevant discipline (Computer Science, ECE, or related).
• Algorithm analysis, data structures, and Python programming proficiency.
• Strong proficiency in PyTorch.
• GPU/CUDA programming proficiency preferred.
• Experience with numerical analysis preferred.

Nice-to-haves

• AutoML and meta-learning.
• C/C++ programming.
• Experience with specialized hardware accelerator systems for DNNs.
• Strong publication record in top ML conferences or journals.
• Experience with numerical analysis.