Helix AI Engineer, Video Pretraining
Figureai•5h ago
United StatesOnsite$200K–$400KFull-timeMid Level5+ yrs exp
Top focus
Ai Engineer
- Figure is an AI robotics company developing autonomous general-purpose humanoid robots. Our goal is to build embodied AI systems that can perceive, reason
- act in the real world. Figure is headquartered in San Jose, CA
- this role requires 5 days/week in-office collaboration.
- 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 US base salary range for this full-time position is between $200,000 - $400,000
- The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills
- 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.
Required skills
PythonPyTorchdeep learningvideo modelingdistributed trainingsoftware engineering