Top Tech Jobs & Startup Jobs in Montreal

Lead architecture and performance exploration for next-generation AI inference accelerators. Build analytical models and simulation frameworks, define subsystem interfaces and roadmaps, and drive hardware/software co-design with compiler, runtime, ML, and silicon teams to optimize latency, throughput, memory, interconnects, power, and cost for evolving LLMs and transformer-based workloads.

Lead physical implementation of AI accelerator ASICs from floorplanning through tapeout. Drive placement, CTS, P&R, signal/IR/EM closure, signoff, and methodology development. Partner with RTL, synthesis, DFT, package, and backend teams to deliver timing, power, area, congestion, and yield targets, and apply AI techniques to optimize QoR.

Lead synthesis, timing convergence, and implementation readiness for AI accelerators. Own synthesis flows, SDC constraints, timing closure, physical-aware optimization, vendor coordination, and apply automation/AI to improve QoR and timing debug across multi-million-gate designs.

Lead power architecture, modeling, optimization, and verification for AI accelerators. Develop lifecycle power models, drive low-power techniques (clock/power gating, voltage islands), own UPF/CPF flows and power-aware verification, partner with cross-functional teams on power integrity and silicon validation, and apply AI tools to improve power analysis and anomaly detection.

Lead pre-silicon emulation strategy for a next-generation AI inference ASIC using Cadence Palladium. Architect multi-rack models, enable software left-shift via hybrid emulation, verify high-speed interfaces and memory hierarchies, perform power/performance analysis, and collaborate with RTL, DV, software teams and Cadence R&D to ensure silicon readiness.