Waabi’s Physical AI platform is powered by state of the art ML models which must be deployed efficiently across diverse use-cases, from onboard vehicle inference to large-scale simulation. As the Distillation Lead, you will own the strategy and execution for distillation across Waabi's AI stack, ensuring our most capable models run efficiently in every deployment context. You will partner closely with ML Platform, Infrastructure, Onboard Autonomy, and Simulation teams to deliver compressed models that meet the performance requirements of both real-time onboard systems and high-throughput simulation pipelines.
You will…
- Define and drive the technical strategy for model distillation and compression across Waabi's AI stack — spanning perception, world models, and planning — with an eye toward both onboard deployment and simulation use-cases.
- Design, implement, and scale state-of-the-art distillation and efficiency pipelines, which may include:
- Distillation for generative models (diffusion, autoregressive, flow-matching, video models)
- Quantization-aware training (QAT) and post-training quantization (PTQ)
- Knowledge distillation (feature-level, response-based, and relation-based)
- Structured and unstructured pruning and sparsification
- Low-rank factorization and efficient architecture design
- Speculative decoding and other inference-time efficiency techniques
- Deep distillation expertise: You have extensive hands-on experience designing and implementing distillation, quantization, pruning, and model compression techniques for large-scale neural networks, with demonstrated impact in production settings.
- Strong research and engineering foundation: A Bachelor's or Master's degree in Machine Learning, Computer Vision, Robotics, or a related field, or equivalent industry experience; relevant hands-on experience in model distillation and efficiency is what matters most. Expert Python and PyTorch (or JAX) skills with experience in large-scale distributed training.
- Technical leadership: You have a proven track record of setting technical direction and driving projects from conception to production. You inspire and elevate those around you through deep technical expertise and mentorship.
- Cross-functional collaboration: You have experience working closely with infrastructure, platform, and autonomy teams to deploy compressed models under real engineering constraints.
- Clear communicator: You can communicate complex technical trade-offs clearly to diverse audiences and drive alignment across research and engineering teams.
- Experience with hardware-aware optimization (TensorRT, ONNX, custom CUDA kernels, hardware-specific quantization).
- Publications at top-tier ML/CV venues (NeurIPS, ICML, CVPR, ICLR, ECCV) in model compression, efficient deep learning, or related areas.
- Experience distilling large generative models (diffusion models, LLMs, VLMs, or video models).
- Background in autonomous vehicles or robotics.
Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve!