Member of Technical Staff - Robotics
- Toronto, ON
- Hybride
- Publié 7 sept. 2026
- 1 poste
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- Type d’emploi
- Temps plein
- Niveau d’expérience
- Intermédiaire · 2+ ans
- Formation minimale
- Baccalauréat
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Exigences de lieu
- Country, Switzerland, United States, Canada
Résumé du poste
You will own the end-to-end policy stack for robotics, including imitation pre-training and RL post-training. Additionally, you will manage on-robot deployment, safety protocols, and real-world evaluation to bridge the gap between simulation and hardware.
Détails du poste
Member of Technical Staff – Robotics About Us Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one. Responsibilities Robotics Systems & Data: Build and maintain robotic systems and data-collection workflows that support research and evaluation. Real-World Experimentation: Design and run hardware experiments to assess performance, robustness, and generalization. Evaluation & Analysis: Develop reproducible benchmarks, investigate failure modes, and use findings to guide model and system improvements. Research Collaboration: Work closely with researchers and engineers to connect advances in machine learning with practical robotics challenges. Requirements PhD degree or equivalent hands-on experience in Robotics, Computer Science, Mechanical or Electrical Engineering, or a related technical field. Experience developing learning-based robot policies and deploying them on real hardware. Strong Python and PyTorch skills, with proficiency in a robot software stack. Solid understanding of robot kinematics, sensing, calibration, and system integration. Ability to independently design, execute, and analyze reproducible robotics experiments. Willingness and ability to travel for hands-on robot setup, testing, and deployment. Nice to Have Experience with manipulation, locomotion, or whole-body control. Experience establishing a robotics lab or data-collection operation from scratch. Experience with imitation learning, reinforcement learning, or robot foundation models. Experience with robotics simulation and transferring learned behaviors across environments. Experience working with multimodal sensor data, teleoperation systems, or tactile and force feedback. Publications or substantial contributions to research on robot learning or embodied AI. Contributions to open-source robotics projects or research infrastructure.
Ce que vous ferez
You will own the end-to-end policy stack for robotics, including imitation pre-training and RL post-training. Additionally, you will manage on-robot deployment, safety protocols, and real-world evaluation to bridge the gap between simulation and hardware.
Exigences
Candidates must have a bachelor's degree in a technical field and hands-on experience deploying robot policies on real hardware. Strong proficiency in Python, PyTorch, and robot software stacks like ROS 2 is required.
Compétences indiquées
- Python · Souhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Robotics
- Python
- PyTorch
- ROS 2
- Kinematics
- Camera-to-robot calibration
- Reinforcement learning
- Imitation learning
- Sim-to-real transfer
- Teleoperation
- Computer vision
- Hardware bring-up
- Control systems
- Isaac Lab
- MuJoCo
- Embodied AI
- Control Loops
- Actuators
- Research
- Artificial Intelligence
- Electrical Engineering
- Calibration
- Computer Science
- Data Collection
- EtherCAT
- Python (Programming Language)
- Mechanical Engineering
- Randomization
- Real-Time Operating Systems
- Remote Operation
- Retargeting
- Robot Operating Systems
- Simulations
- System Identification
- Tokenization
- Troubleshooting (Problem Solving)
- PyTorch (Machine Learning Library)
Domaines d’emploi
- Technology
- Engineering
- Science & Research
- Software
- Data & Analytics
- Member of Technical Staff
- Artificial Intelligence Engineer (General)
- Software Developers
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