2026 Summer Intern, MS/PhD, ML Compute, Hardware Engineer
About the position Responsibilities • Design a hardware-friendly algorithm for compressing activations, weights and instructions in an ML accelerator • Develop a proof-of-concept hardware implementation of the compressor-decompressor • Study trade-offs between hardware complexity, performance, compression loss • Collaborate with ML model owners to estimate impact of compression on model quality Requirements • Enrolled in a Masters program in Electrical Engineering, Computer Engineering or equivalent • Strong understanding of computer architecture for domain-specific accelerators • Strong programming skills in C++ and/or Python • Proficiency in digital design using High-level synthesis, SystemVerilog or similar languages Nice-to-haves • Enrolled in a PhD program in Electrical Engineering, Computer Engineering or equivalent • Understanding of ML numerics, error analysis and model quality evaluations • Experience with domain-specific languages for hardware design (Eg. Chisel, Magma etc.) • Familiarity with high-level architectural simulators such as Gem5 Apply tot his job Apply tot his job