AI Accelerator, Software Engineer- Graph Optimization/Compilers

Ampere is a semiconductor design company focused on high-performance, energy-efficient computing for AI, cloud, and edge applications. The Software Engineer will optimize deep learning computational graphs and models for Ampere’s AI accelerator hardware, working across frameworks, compilers, runtimes, kernels, and performance infrastructure.

Responsibilities:

• Optimize computational graphs for performance, throughput, latency, memory efficiency, and power efficiency on Ampere AI accelerators
• Enable and optimize models, frameworks, and inference platforms, including PyTorch, Llama.cpp, vLLM, and SGLang
• Develop graph-level optimizations such as operator fusion, pattern matching, redundancy elimination, constant folding, layout optimization, memory planning, quantization, and accelerator offload
• Optimize transformer and LLM workloads, including dynamic shapes, attention mechanisms, KV-cache management, and mixed-precision execution
• Analyze end-to-end performance across frameworks, compilers, runtimes, kernels, and hardware
• Build profiling, benchmarking, validation, and performance-regression infrastructure
• Identify bottlenecks using traces, compiler diagnostics, microbenchmarks, and hardware performance data
• Collaborate with compiler, runtime, kernel, architecture, hardware, and applications teams on hardware/software co-design
• Contribute to architecture, design reviews, code reviews, documentation, and engineering best practices