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Lead Robotics and Autonomy Specialist
2 months ago
Position Overview
As a key contributor to the R&D division, the Lead Robotics and Autonomy Specialist will spearhead the advancement of innovative AI solutions for robotic systems, empowering them to understand, learn, and navigate intricate environments effectively.
Key Responsibilities
- Skillfully apply machine learning methodologies, SLAM, motion planning, and robotic perception to ensure safe navigation in challenging settings.
- Investigate and analyze cutting-edge technologies in machine learning, SLAM, and motion planning; suggest novel research pathways.
- Create adaptive algorithms that enable robots to learn from human interactions.
- Implement and deploy solutions across the robotic fleet; evaluate real-world performance through comprehensive data analysis.
- Provide mentorship and guidance in the realms of robotics, machine learning, and associated software development.
- Research and innovate supervised, unsupervised, and reinforcement learning algorithms for the analysis of robotic fleet data.
- Design algorithms to improve robotic perception, mapping, and motion planning across diverse hardware platforms.
- Contribute expertise in developing software frameworks and tools to enhance robotics research efficiency.
Qualifications
- Master’s or Ph.D. in Computer Science, Software Engineering, or a related discipline.
- Extensive experience with SLAM, Perception, or Motion Planning algorithms.
- Minimum of 4 years of professional experience in embodied AI (e.g., robotics, autonomous vehicles).
- Strong foundation in machine learning techniques (unsupervised, supervised, reinforcement, demonstration) and optimization algorithms.
- Proficient programming skills in Python and C++ within a Linux environment.
- Significant experience translating research findings into practical implementations.
- Proficiency in deep learning frameworks (e.g., TensorFlow, PyTorch).
- Experience in designing and developing robotic systems utilizing robotic middleware (e.g., ROS) and existing libraries/tools.
- Proven history of research excellence or the application of research into real-world solutions.
- Familiarity with continuous integration, deployment, and release management tools.
- Understanding of Agile and Scrum methodologies.
- Strong skills in system integration and software architecture.
- Experience in launching products that incorporate embedded machine learning algorithms.
Compensation
$140-175K
