For a stealth project we are seeking a Robotics Researcher with a strong foundation in data-driven generalist models to advance our efforts in large-scale multimodal data collection curation and model training for robotics. You will contribute to the development of systems that enable robots to generalize across tasks environments and sensor modalities.
Tasks
Responsibilities
- Design and implement pipelines for large-scale robotics data collection and annotation (video egocentric 3D simulation).
- Develop and evaluate generalist models for perception control and world modeling using collected data.
- Automate dataset ingestion cleaning and integration from heterogeneous sources (simulation real-world sensors public datasets).
- Collaborate on benchmarking dataset standardization and metadata schema design for robotics datasets.
- Integrate multimodal data (RGB depth IMU tactile) into unified model training workflows.
- Prototype and train models across manipulation mobility and navigation domains using state-of-the-art frameworks.
- Contribute to open-source toolkits evaluation benchmarks and internal research reports.
Requirements
Requirements
- Strong background in computer vision machine learning or embodied AI.
- Experience with model training (transformers diffusion or imitation/RL models).
- Proficiency in Python and familiarity with PyTorch TensorFlow or JAX.
- Experience working with large datasets (e.g. manipulation simulation egocentric).
- Understanding of ROS Gazebo Isaac Sim or similar robotics ecosystems.
- Strong collaborative and documentation skills.
For a stealth project we are seeking a Robotics Researcher with a strong foundation in data-driven generalist models to advance our efforts in large-scale multimodal data collection curation and model training for robotics. You will contribute to the development of systems that enable robots to gene...
For a stealth project we are seeking a Robotics Researcher with a strong foundation in data-driven generalist models to advance our efforts in large-scale multimodal data collection curation and model training for robotics. You will contribute to the development of systems that enable robots to generalize across tasks environments and sensor modalities.
Tasks
Responsibilities
- Design and implement pipelines for large-scale robotics data collection and annotation (video egocentric 3D simulation).
- Develop and evaluate generalist models for perception control and world modeling using collected data.
- Automate dataset ingestion cleaning and integration from heterogeneous sources (simulation real-world sensors public datasets).
- Collaborate on benchmarking dataset standardization and metadata schema design for robotics datasets.
- Integrate multimodal data (RGB depth IMU tactile) into unified model training workflows.
- Prototype and train models across manipulation mobility and navigation domains using state-of-the-art frameworks.
- Contribute to open-source toolkits evaluation benchmarks and internal research reports.
Requirements
Requirements
- Strong background in computer vision machine learning or embodied AI.
- Experience with model training (transformers diffusion or imitation/RL models).
- Proficiency in Python and familiarity with PyTorch TensorFlow or JAX.
- Experience working with large datasets (e.g. manipulation simulation egocentric).
- Understanding of ROS Gazebo Isaac Sim or similar robotics ecosystems.
- Strong collaborative and documentation skills.
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