Research Engineer – World Models

About the role

Waabi’s autonomous‑driving stack is powered by Waabi World. As a Research Engineer in the World Models team you will develop algorithms and productionize the next generation of world models that can reason about complex, dynamic 4D environments.

Key responsibilities

• Design, implement, and scale state‑of‑the‑art generative and predictive world‑modeling systems, including video generation, latent diffusion, multimodal foundation models, and LLM/VLM/VLA methods.
• Collaborate with research scientists to turn prototype models into robust, large‑scale training and inference pipelines.
• Optimize model training and inference for efficiency, speed, and reliability on massive datasets.
• Build large‑scale data pipelines to create high‑quality datasets for training.
• Maintain the stability and maintainability of the world‑model codebase and infrastructure.

Required profile

• Strong software‑engineering skills with extensive Python and PyTorch (or JAX) experience, plus expertise in distributed training and large‑scale model deployment.
• Master’s degree in Computer Vision, Machine Learning, Robotics, or a related field, or equivalent industry experience.
• Proven experience building and deploying generative or predictive models of physical environments at scale.
• Demonstrated ability to work effectively in a close‑knit team of researchers and engineers.

Required skills

• Python
• PyTorch or JAX
• Distributed training frameworks
• Large‑scale model deployment
• Video generation and prediction models
• Latent diffusion, autoregressive, flow‑matching techniques
• Multimodal foundation models for driving scenes
• LLM, VLM, VLA methods
• Model distillation
• Data pipeline construction
• Cloud platforms, Kubeflow, Ray
• ONNX, TensorRT