AI Accelerator Design Verification Engineer - Full Time

What you'll do

• Develop verification plans for AI accelerator blocks: tensor processing, fabric / network-on-chip, and SoC flows
• Write and debug SystemVerilog/UVM testbenches, checkers, stimulus, scoreboards, and reference models for your assigned block or subsystem
• Build emulation-friendly testbenches: synthesizable, transactor-based environments that run the same tests in simulation and on emulators or FPGA prototypes
• Use agentic AI tools across the verification workflow: generating test plans from specifications, writing and reviewing testbench code, triaging regression failures, root-causing bugs, and analyzing coverage. Review and validate everything the agents produce.
• Verify numerical correctness of compute datapaths (FP*) against bit-accurate golden models
• Run real ML kernels and random programs on the RTL, co-simulated against an ISA/architectural reference model
• Define, implement, and close functional and code coverage goals, analyzing holes and driving them to closure
• Debug failures across RTL, testbench, and reference models, and work with RTL designers to root-cause and resolve bugs
• Apply formal verification, assertions (SVA), and emulation where appropriate to improve verification quality and efficiency
• Run and maintain regressions across simulation, emulation, and FPGA platforms, and track bug trends and verification progress metrics
• Partner with RTL design, performance modeling, CAD/methodology, and software teams to align on verification strategy, improve tools and flows, and drive shared quality, schedule, and tape-out goals
• Participate in microarchitecture, RTL, and verification reviews, and write technical documentation

What we're looking for

• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science or a related field.
• Strong foundation in AI accelerator and computer architecture and digital design, with solid understanding of following:
• Tensor cores and SIMT / SIMD / vector processing
• Floating-point / computer arithmetic, including reduced-precision formats
• On-chip memories, scratchpads, and DMA engines
• Cache hierarchy, memory systems, and HBM/DRAM interfaces
• Network-on-chip and on-chip interconnects
• Dataflow, scheduling, and synchronization across many compute cores
• Working knowledge of modern AI accelerator flows and ISAs, including familiarity with ISA simulators or reference models
• Proficiency in System Verilog, C/C++, assembly
• Familiarity with emulation-friendly verification (synthesizable testbenches, transactors) is a plus
• Hands-on experience using agentic AI tools across the engineering workflow: delegating multi-step tasks to agents, writing clear instructions and context, and checking their results critically
• Scripting experience for automation, test generation, regression management, or data analysis, such as Python, Tcl, or Rust
• Exposure to ML frameworks or workloads (PyTorch, TensorFlow, or ONNX) is a plus