Senior/Staff Research Engineer -- Vision-Language-Action Models (Autonomous Driving)
| Verified Pay check_circle | Provided by the employer$170000 - $260000 per year |
|---|---|
| Hours | Full-time |
| Location | Santa Clara, California |
About this job
Job Description
You will join our core AI team at the frontier of autonomous decision-making, building the Vision-Language-Action (VLA) models that form SuperDrive's reasoning layer. You'll train VLA models that generate high-level driving decisions and trajectory guidance for on-board strategic decision-making, and design the knowledge distillation and compression techniques that transition large models onto on-board compute.
- Design, train, and evaluate Vision-Language-Action models that generate high-level driving decisions and trajectory guidance in support of Plus's reasoning layer.
- Own a VLA workstream end to end — data, architecture, large-scale training, and on-vehicle validation.
- Build training and evaluation pipelines and rigorous metrics for VLA performance in driving contexts.
- Develop distillation and compression recipes to deploy large reasoning models on on-board compute.
- Apply SFT and RL post-training to improve reasoning, robustness, and long-tail behavior.
- Collaborate with perception, planning, and platform teams to bring models from research to production
- M.S. minimum, Ph.D. preferred in CS, EE, Mathematics, Statistics, or a related field.
- 3+ years implementing and training models in a deep learning framework (PyTorch, TensorFlow, or JAX).
- Direct, hands-on experience training vision-language / vision-language-action models.
- Hands-on experience with model training, evaluation, and deployment in production.
- Thorough understanding of state-of-the-art vision-language / VLA models, diffusion, flow matching, and transformers.
- Experience with large-scale / distributed model training.
- Model distillation, quantization, and inference optimization (ONNX/TensorRT, mixed precision, custom kernels).
- SFT and RL post-training of large multimodal models.
- Hands-on experience with multi-modal sensor data (camera, LiDAR, radar).
- Publications at top venues (CVPR, NeurIPS, ICML, ICLR, CoRL, RSS, ICRA).
- Autonomous driving / ADAS experience.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Your Privacy Choices