Senior AI Software Architect - Autonomous Systems

AMD AMD · Semiconductors · Austin, TX · Engineering

Senior AI Software Engineer responsible for designing, implementing, and optimizing AI-driven software solutions for autonomous systems, focusing on model optimization, inference pipelines, GPU acceleration, and system performance profiling for edge and cloud deployments.

What you'd actually do

  1. Select and optimize AI models for autonomous applications, ensuring scalability, low latency, and real-time performance across edge and cloud deployments.
  2. Collaborate with cross-functional teams to ensure seamless integration of AI frameworks into software stacks, optimizing inference pipelines and model performance for real-world use cases.
  3. Provide technical leadership and guidance in AI software best practices, focusing on deep learning frameworks, GPU-accelerated computing, model compression, and efficient deployment strategies for autonomous systems.
  4. Analyze and optimize AI software stack performance, particularly in real-time inference, GPU-accelerated, and autonomous navigation environments, identifying bottlenecks and implementing targeted improvements.
  5. Stay updated with the latest trends and technologies in AI frameworks, foundation models, edge AI deployment and autonomous systems integration, offering insights and recommendations to continuously advance AI capabilities.

Skills

Required

  • PyTorch
  • TensorFlow
  • JAX
  • ONNX Runtime
  • model profiling
  • benchmarking
  • quantization
  • pruning
  • distillation
  • ROCm
  • CUDA programming
  • GPU kernel optimization
  • GPU memory management
  • NVIDIA Nsight
  • TensorRT
  • Triton Inference Server
  • ROS/ROS2
  • edge AI hardware platforms

Nice to have

  • foundation models

What the JD emphasized

  • deep expertise in AI frameworks
  • model analysis and optimization
  • GPU-accelerated computing
  • system performance profiling
  • real-time inference
  • autonomous systems integration

Other signals

  • designing and implementing AI-driven software solutions
  • model analysis and optimization
  • GPU-accelerated computing
  • system performance profiling
  • real-time inference
  • autonomous systems integration