Optimize Waabi’s distributed machine learning training with profiling, CUDA, and inference technologies across research and production.

This Senior or Staff engineering role focuses on creating stable, efficient training frameworks for Waabi’s autonomous transportation technology. You will investigate CPU and GPU performance, assess quantization-aware training, and explore compilation and deployment techniques. Collaboration with researchers and machine learning engineers will guide optimal resource usage and practical adoption through tooling and dashboards.

Key Responsibilities:

- Drive distributed training toward greater stability and efficiency
- Comprehensively profile runtime and memory performance
- Identify technologies for training and inference frameworks




- Design current CUDA kernels when appropriate
- Improve dashboards that encourage broad tool adoption

Requirements:

- Computer Science, Robotics, or similar technical education
- Minimum four years industry experience with bachelor's degree
- Strong coding skills across Python, C++, or Rust
- Deep learning framework experience with PyTorch or Jax
- Profiling experience with PyTorch Profiler or NVIDIA Nsight

Bring distributed training, performance profiling, and framework optimization experience to Waabi’s growing engineering team.

📌 Staff Distributed Training Optimization Engineer (Toronto)
🏢 Waabi
📍 Toronto