Our Helix team is responsible for developing the core AI systems that power humanoid autonomy. We are looking for a
Helix AI Engineer, Video Pretraining to lead the development of large-scale video foundation models trained on diverse real-world and robot-collected data.
This role focuses on pretraining models that learn from raw video-capturing motion, interaction, and temporal structure-to enable downstream capabilities in perception, prediction, and embodied reasoning.
Responsibilities- 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
- Build models that learn transferable representations for downstream tasks such as perception, tracking, prediction, and control
- 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
- Optimize model performance across compute, memory, and training efficiency constraints
- 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
Requirements- 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
- Experience with large-scale pretraining, including dataset curation, training dynamics, and scaling laws
- 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
- Solid software engineering skills and ability to build scalable, reliable systems
- Ability to operate independently and drive ambiguous, high-impact research directions
Bonus Qualifications- Experience working on frontier video models or multimodal foundation models
- Background in video diffusion, autoregressive video modeling, or world models
- Experience at leading AI labs such as OpenAI, Google DeepMind, Google, ByteDance, Midjourney, or Adobe
- Experience with large-scale dataset construction and filtering for video pretraining
- Familiarity with robotics, embodied AI, or learning from egocentric / first-person video
- Publication record in machine learning, computer vision, or multimodal AI
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.
