pythonc++roboticsvision language modelsuncertainty quantificationsemantic mappingros 2active perception
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Это четко сфокусированная исследовательская роль в робототехнике с работой на реальных роботах и современным стеком, но без диапазона зарплаты сложно оценить компенсацию относительно рынка.
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Зарплата не указанаСовременный стекРобототехника и ИИИсследования на роботах
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Текст:
Hirify AI/Оригинал
TL;DR
Robotics Applied Scientist (Active Perception) (Robotics/AI): Developing active perception, viewpoint planning, and calibrated vision-language reasoning for real robots with an accent on information gathering, uncertainty, and field-ready deployment. Focus on running research through real-world experiments, shaping technical roadmaps, and mentoring collaborators.
Location: On-site in Irvine, California, United States
Company
hirify.global develops risk-aware, reliable, field-ready embodied AI systems for real robots, sensors, and deployments.
What you will do
Formulate active perception problems for inspection and a broad range of robot behaviors.
Develop viewpoint planning policies for active information gathering.
Research calibrated confidence and abstention for vision-language reasoning on robots.
Lead research and development through real-world experiments that demonstrate feasibility and deployability.
Investigate and shape the technical roadmap by aligning real-world needs with technical development.
Mentor junior team members and collaborators.
Requirements
PhD in robotics, computer science, electrical engineering, aerospace engineering, mechanical engineering, or a related field.
Publications at top venues such as RSS, CoRL, ICRA, IROS, T-FR, T-RO, CVPR, NeurIPS, or similar.
Research experience in active perception, informative path planning, vision-language models, or semantic mapping for exploration.
Hands-on experience with vision-language or foundation models for robot perception, including the physical principles governing them.
Fluency in Python and the ability to run methods on real robots using C++ and ROS 2.
Fluency with uncertainty, including Bayesian or information-theoretic planning, calibration, and conformal methods.
Nice to have
Real-robot experience in the wild.
Experience with metric-semantic scene graphs, open-vocabulary mapping, or spatio-temporal scene representations.
Experience fine-tuning or deploying compact vision-language models on edge computers.
Exposure to robotic industrial inspection workflows.
Culture & Benefits
Work directly with real robots, sensors, and field deployments.
Develop systems that are tested on hardware and improved through real-world operation.
Combine rigorous engineering with learning systems used in globally deployed solutions.
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