MACHINE LEARNING RESEARCH ENGINEERAbout us -d-Matrix is building a novel hardware system and a full-stack software solution to accelerate large-scale modern deep neural network compute workloads for the cloud. -Leveraging a unique combination of in-memory compute, digital signal processing system, on-chip and chip-to-chip interconnect fabric design, d-Matrix's AI compute engine holds the promise of drastically improving the power efficiency and compute latency of cloud inference workloads, by orders of magnitude compared to competition. -Why d-Matrix -We want to build a company and a culture that sustains the tests of time. -We offer the candidate a very unique opportunity to express themselves and become a future leader in an industry of global influence. -We strive to build a culture of transparency, inclusiveness and intellectual honesty while ensuring that all our team members are always learning and having fun on the journey. -The candidate will get to work on path-breaking innovations with a highly experienced team that knows what it takes to build a successful business.The role: Machine Learning Research EngineerThe Machine Learning Team is responsible for the R&D of core algorithm-hardware co-design capabilities in d-Matrix's end-to-end solution. -You will be joining a team of exceptional people enthusiastic about researching and developing state-of-the-art efficient deep learning techniques tailored for d-Matrix's AI compute engine. -You will also have the opportunity of collaboration with top academic labs and help customers to optimize and deploy workloads for real-world AI applications on our systems. -Responsibilities ---- Design, implement and evaluate efficient deep neural network architectures and algorithms for d-Matrix's AI compute engine.--- Engage and collaborate with internal and external ML researchers to meet R&D goals. ---- Engage and collaborate with SW team to meet stack development milestones. ---- Conduct research to guide hardware design. ---- Develop and maintain tools for high-level simulation and research. ---- Port customer workloads, optimize them for deployment, generate reference implementations and evaluate performance. ---- Report and present progress timely and effectively. ---- Contribute to publications of papers and intellectual properties. -Qualifications -Minimum:--- Master's degree in Computer Science, Electrical and Computer Engineering, or a related technical discipline. ---- High proficiency with major deep learning frameworks: PyTorch, TensorFlow is a must. ---- High proficiency in algorithm analysis, data structure, and Python programming is a must. -Desired:--- Proficiency with C/C++ programming is preferred. ---- Proficiency with GPU CUDA programming is preferred.--- Deep, wide and current knowledge in machine learning and modern deep learning is preferred --- Experience in real-world data science projects in an industry setting is preferred. ---- Experience with efficient deep learning is preferred: quantization, sparsity, distillation. ---- Experience with specialized HW accelerator systems for deep neural network is preferred. ---- Passionate about AI and thriving in a fast-paced and dynamic startup culture.
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