Top Tech Jobs & Startup Jobs

Design and validate modular electromechanical chassis and rack-level systems for data centers (HPC/AI/Enterprise). Own product lifecycle through high-volume manufacturing, perform thermal/structural/vibration analysis using FEA, specify metal fabrication and liquid/power connector integration, and align across silicon, power, and optical teams.

Lead architecture and integration of the SoC management subsystem: ARM core integration, PCIe and memory interfaces, peripherals, debug/trace, control paths, and cross-team co-design to meet performance, power, and area targets.

Design, develop, and optimize embedded software for AI-enabled devices. Integrate AI algorithms with hardware, improve system performance, validate and test AI features, document designs, maintain version control, and support deployment and troubleshooting of embedded AI systems.

Design, develop, and optimize core components of an AI-driven software stack. Implement API layers, command pipelines, and memory management; collaborate with hardware and kernel teams; debug across user-to-hardware layers; and optimize for performance and throughput.

Verify chip-level and performance behavior of custom ASICs: design end-to-end test flows with architecture team, run simulation-based verification, implement UVM environments, use constrained-random and functional-coverage methodologies, and coordinate vendors/contractors.

Develop and maintain system-level performance simulators and models for AI/data-intensive workloads; characterize real workloads (LLMs, GNNs, graph analytics); model memory, interconnect, and scheduling behavior; evaluate architectural trade-offs and produce quantitative comparisons; collaborate with hardware architects, compiler/runtime teams, partners, and stakeholders; translate performance modeling into clear narratives for technical and executive audiences.

Design, implement, and optimize compiler components for AI models targeting CPUs, GPUs, and custom accelerators. Enhance PyTorch Inductor/Dynamo, Triton, LLVM, and MLIR toolchains; create IRs, codegen passes, and performance optimizations; profile and tune kernels; and contribute to open-source projects.