ML Architect, Compute

About the Role In this role, you will report to a Hardware Engineering Manager. Responsibilities Analyze workloads and map them efficiently to hardware, proposing novel HW-friendly implementations and projecting performance Architect, simulate and design amazing machine learning solutions for our autonomous driving technology Work closely with compiler and model developers to influence engineering trade-offs and future model architectures Build scalable tools for simulator modeling and performance evaluation Interact with cross-functional engineering teams to identify opportunities and requirements Requirements BS degree in Computer Science or Computer Engineering or similar relevant technical field, or equivalent practical experience 3+ years on designing/architecting complex, high performance architectures - CPUs, GPUs and/or ML accelerators - in the industry or through doctoral research 1+ years experience with machine learning architectures, acceleration and model optimization Strong C++ programming and algorithmic problem solving skills Preferred Qualifications 1+ years modeling high performance architectures architectures in cycle-aware simulators Track record of analyzing workloads and architecting, delivering novel HW+SW solutions to vastly improve performance, efficiency Familiarity with ML model architectures and their compute characteristics (bottlenecks, optimization opportunities) Experience with microarchitecture design (SystemVerilog or HLS) #J-18808-Ljbffr Gravity Engineering Services Pvt Ltd.