Helix AI Engineer, Video Pretraining

Responsibilities

• Design and train large-scale video foundation models using internet-scale and robot-collected data
• Develop pretraining strategies to capture temporal dynamics, motion, and object interaction
• Build models that learn transferable representations for perception, tracking, prediction, and control
• Explore transformer-based and diffusion-based architectures for video understanding and generation
• Implement efficient data pipelines and training strategies for high-throughput distributed training
• Optimize model performance across compute, memory, and training efficiency constraints
• Collaborate with generative modeling and robot learning teams to integrate models into the autonomy stack
• Design evaluation frameworks to measure temporal understanding and generalization

Requirements

• Experience training large-scale models on video data or high-dimensional sequential modalities
• Strong understanding of modern deep learning architectures for vision or multimodal systems
• Experience with large-scale pretraining, dataset curation, 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
• Solid software engineering skills to build scalable, reliable systems
• Ability to operate independently and drive high-impact research directions

Preferred 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 (e.g., OpenAI, Google DeepMind, ByteDance)
• Experience with large-scale dataset construction and filtering
• Familiarity with robotics, embodied AI, or learning from egocentric video
• Publication record in machine learning, computer vision, or multimodal AI

About the Company

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. Our goal is to build embodied AI systems that can perceive, reason, and act in the real world.