Remote PnP Optimization Engineer en Waabi
Waabi · San Francisco, CA, Dallas, TX, Toronto, CAN & Remote - US & Canada, Estados Unidos De América · Remote
Waabi, founded by AI pioneer and visionary Raquel Urtasun, is an AI company building the next generation of self-driving technology. With a world class team and an innovative approach that unleashes the power of AI to “drive” safely in the real world, Waabi is bringing the promise of self-driving closer to commercialization than ever before. Waabi is backed by best-in-class investors across the technology, logistics and the Canadian innovation ecosystem.
With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai
You will…
- Collaborating with research scientists during algorithm design to ensure code is efficiently designed from inception
- Identify and communicate best practices for model development
- Reformulate performance bottlenecks
- Develop a framework suitable for mixed precision training of multi-task, multi-modality models in a heterogeneous distributed training environment
- Research, implement, and test alternative formulations for fundamental DNN operations and AV centric representations
- Enable safe and efficient deployment of PnP models
Qualifications:
- PyTorch API and implementation
- CUDA system design
- Asynchronous programming model
- Heterogeneous compute
- C++ / libtorch
Bonus:
- Machine learning model architecture design
- TensorRT
- CUDA kernel implementation
- Experience with autonomous vehicle multi-sensor model architectures
