skills

Technical expertise across production AI, intelligent infrastructure, and efficient inference.

AI systems

  • AI inference and serving
  • Distributed AI systems
  • Hardware/software co-optimization
  • Multi-agent orchestration
  • MLOps and production monitoring

Machine learning

  • Deep learning and computer vision
  • 3D human pose estimation and human motion understanding
  • Self-supervised learning and foundation models
  • Vision Transformers and discrete tokenization
  • Time-series modeling and signal processing
  • Model optimization and edge inference

Languages and frameworks

  • Python, C/C++, CUDA, Java, and SQL
  • PyTorch, TensorFlow, ONNX, and LangChain

Platforms and infrastructure

  • Hybrid edge/cloud AI
  • NVIDIA Jetson, FPGA, and resource-constrained devices
  • AWS and AWS Lambda
  • Kubernetes, Docker, and Terraform
  • Linux, GitHub Actions, and Git