Helix AI Engineer, Video Pretraining

Experience training large-scale models on video data or other high-dimensional sequential modalities

Strong understanding of modern deep learning architectures for video, vision, or multimodal systems

Proficiency in Python and deep learning frameworks such as PyTorch

Experience working with distributed training systems and large GPU clusters

Strong experimental rigor and ability to iterate quickly on model design and training strategies

Experience working on frontier video models or multimodal foundation models

Design and train large-scale video foundation models on diverse datasets spanning internet-scale video and robot-collected data

Develop pretraining strategies that capture temporal dynamics, motion, and object interaction from raw video sequences

Explore architectures for video understanding and generation, including transformer-based and diffusion-based approaches

Implement efficient data pipelines and training strategies for high-throughput video ingestion and large-scale distributed training

Collaborate closely with generative modeling, agent, and robot learning teams to integrate pretrained models into the autonomy stack

Design evaluation frameworks and benchmarks to measure temporal understanding, prediction quality, and generalization