Back to SearchSenior Staff Applied Scientist - AI & Robotics
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Join our AI Research team to develop advanced robot policies for dexterous manipulation in real-world environments. As a Senior Applied Scientist, you will lead the design, training, and deployment of robot learning models that integrate multimodal perception, policy learning, and physical execution. Collaborate with cross-functional teams to push the boundaries of embodied AI and solve industrial-scale challenges in autonomy and simulation.
Responsibilities
- Design, implement, and deploy advanced robot learning models and policy architectures for manipulation and autonomous task sequencing, integrating multimodal sensory data, perception, planning, and execution on robotic platforms using ROS/ROS2
- Develop and optimize end-to-end policy training pipelines, including policy inference and closed-loop control systems, for real-world and simulated environments
- Lead data strategy for demonstrations, teleoperation, simulation pipelines, and evaluation frameworks to ensure robust, repeatable, and safe robot policy deployment
- Collaborate with cross-functional teams and AI infrastructure experts to deploy scalable, production-ready robotics systems
- Stay current with embodied AI research, contribute to reproducible research, and share insights through mentorship and technical presentations
- Optimize PyTorch implementations, including custom modules and performance tuning, for efficient model deployment
Requirements
- PhD in a relevant STEM field or Master’s with equivalent industry experience in robotics or embodied AI
- 3+ years of experience building and deploying machine learning models on robotic systems, including integration of multimodal sensory data and control outputs
- Deep knowledge of modern AI architectures (e.g., Transformers, diffusion models, VLM/VLAs)
- Strong PyTorch skills, with experience authoring custom modules and optimizing performance
- Practical experience with Robot Operating System (ROS/ROS2) and policy integration
- Proven impact through publications, open-source contributions, or production deployments
- Ability to lead complex projects involving cross-functional collaboration
- Strong problem-solving, analytical, and communication skills (English proficiency: C1)
Nice to have
- Experience in computer vision on 3D data, including perception and affordance modeling
- Familiarity with simulation platforms such as Isaac Sim, Mujoco, Gazebo, or PyBullet
- Expertise in dexterous manipulation and multi-step autonomous task execution
- Knowledge of visual trends and their application to embodied AI tasks
- Experience adapting foundation models for embodied control and instruction-following agents