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Build cycle-level Python performance models of AI inference workloads for a novel GPNPU. Model tensor placement, tiling, memory hierarchy, sharding, and communication. Calibrate models against simulators and traces, analyze trade-offs (latency vs throughput), and produce technical studies that inform architecture and product decisions.

The AI Inference Engineer will port, optimize, and benchmark AI models for Quadric's platform while providing support and documentation.

The AI Kernel Engineer will develop and optimize AI kernels for Quadric's platform, enhancing performance across various hardware configurations and providing technical support.

The Design Verification Intern will assist in verifying CPU/GPU designs, collaborate on test plans, and debug tests. Familiarity with verification methodologies is required.

As a Senior Hardware Engineer, you will define processor architecture, implement microarchitecture in SystemC/SystemVerilog, and optimize PPA across design cycles.

Lead the quality assurance for AI software, defining test strategies, managing a team, ensuring compliance with safety standards, and utilizing automated testing tools.

As a Deep Learning Compiler Engineer, you will own compiler passes, debug compilation issues, collaborate with teams, and improve compiler performance for edge devices.

The AI Applications Engineer will lead technical support initiatives, develop demos and benchmarks, and provide customer training using Quadric's SDK. This role requires expertise in system architecture and optimization strategies, along with strong coding skills and the ability to troubleshoot complex issues.

As a Senior Deep Learning Compiler Engineer, you will optimize neural networks and develop algorithms for Quadric’s architecture, focusing on performance enhancement through advanced mathematical and algorithmic techniques.

The role involves architecting and developing test benches for GPNPU processors, collaborating on verification plans, implementing testbenches, and tracking verification progress using metrics.