
51 - 200 employees
💰 $110M Series B on 2023-09
d-Matrix is building a new way of doing datacenter AI inferencing using in-memory computing (IMC) techniques with chiplet level scale-out interconnects. Founded in 2019, d-Matrix has attacked the physics of memory-compute integration using innovative circuit techniques, ML tools, software and algorithms; solving the memory-compute integration problem, which is the final frontier in AI compute efficiency.
🕒 February 9
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51 - 200 employees
💰 $110M Series B on 2023-09
d-Matrix is building a new way of doing datacenter AI inferencing using in-memory computing (IMC) techniques with chiplet level scale-out interconnects. Founded in 2019, d-Matrix has attacked the physics of memory-compute integration using innovative circuit techniques, ML tools, software and algorithms; solving the memory-compute integration problem, which is the final frontier in AI compute efficiency.
• Be part of the team that helps productize the SW stack for our AI compute engine. • Responsible for the development, enhancement, and maintenance of software kernels for next-generation AI hardware. • Possess experience building software kernels for HW architectures. • Build and scale software deliverables in a tight development window. • Collaborate 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.
• MS in computer engineering, math, physics, or a related degree with 5+ years of industry experience or PhD in computer engineering, math, physics, or a related degree with 1+ years of industry experience • Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals • Proficient in C/C++ and Python development in Linux environments and using standard development tools • Experience implementing algorithms in high-level languages such as C/C++ and Python. • Experience implementing algorithms for specialized hardware such as FPGAs, DSPs, GPUs, and AI accelerators using libraries such as CUDA, etc. • Experience in implementing operators commonly used in ML workloads—GEMMs, Convolutions, BLAS, SIMD operators for operations like softmax, layer normalization, pooling, etc. • Experience with development for embedded SIMD vector processors such as Tensilica. • Self-motivated team player with a strong sense of ownership and leadership • Prior startup, small team, or incubation experience (preferred) • Experience with ML frameworks such as TensorFlow and/or PyTorch (preferred) • Experience working with ML compilers and algorithms, such as MLIR, LLVM, TVM, Glow, etc. (preferred) • Work experience at a cloud provider or AI compute/subsystem company (preferred)
• hybrid, working onsite at our Bangalore, India, offices 3-5 days per week.
Apply Now🕒 February 9
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