- Mountain View, California, United States
- Hybrid
- Full-time · Senior
- $120K–$235K per year
- 3+ years
Develop and enhance analytical performance models and simulation frameworks for AI accelerators, GPU architectures, and large-scale AI systems.
Compensation
Hardware Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Responsibilities
- Develop and enhance analytical performance models and simulation frameworks for AI accelerators, GPU architectures, and large-scale AI systems.
- Model end-to-end AI training and inference workloads, including compute kernels, attention, MoE, memory access patterns, and communication operations.
- Evaluate new architectural features, compute and memory hierarchies, interconnects, and collective communication mechanisms to identify performance and efficiency improvements.
- Perform workload mapping and parallelization analysis across tensor, pipeline, expert, data, and context parallelism strategies to optimize accelerator utilization and scalability.
- Develop system-level performance models to evaluate throughput, latency, perf/W, and TCO across accelerator, rack, and cluster configurations.
Requirements
- Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field
- Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field