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2026 Summer Intern – PhD – Behaviors
Исключительная возможность для PhD-студентов поработать в лидирующей компании индустрии беспилотников с доступом к уникальным данным. Высокий потенциал для публикаций и карьерного роста в престижной среде.
Сложность вакансии
Высокая сложность обусловлена требованием статуса докторанта (PhD) и наличием публикаций в топовых конференциях (CVPR, NeurIPS и др.). От кандидата ожидается глубокая научная экспертиза в узкой области автономного вождения.
Анализ зарплаты
Зарплата для PhD-интернов в области ML в США обычно выше среднего по рынку стажировок и сильно зависит от локации (Бостон/Питтсбург). Указанные рыночные оценки отражают стандартные компенсационные пакеты в крупных технологических компаниях и R&D центрах.
Сопроводительное письмо
I am writing to express my strong interest in the 2026 Summer Intern – PhD – Behaviors position at Motional. As a PhD candidate specializing in Machine Learning and Robotics, I have long admired Motional’s contributions to the field, particularly the development of benchmarks like nuScenes and nuPlan. My research focus on motion prediction and agent simulation aligns perfectly with your team's mission to deliver high-quality, scientifically rigorous ML technologies for autonomous vehicles.
With a solid background in PyTorch and a track record of publications in top-tier conferences such as CVPR and NeurIPS, I am confident in my ability to contribute to your research on Vision-Language-Action models and scenario generation. I am particularly excited about the opportunity to work with your large-scale real-world datasets and collaborate with cross-functional teams to see research results deployed on actual autonomous vehicles. I look forward to the possibility of bringing my technical expertise and collaborative mindset to your Boston or Pittsburgh office.
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Описание вакансии
Mission Summary:
We are looking for a highly motivated intern to join our Behaviors team and conduct research on Machine Learning for prediction and planning. Here, you will work with the team behind nuScenes, nuPlan, PBP Trajectory Prediction and DriveIRL to deliver ML technologies aligned with the core values of Motional, ensuring the highest standards of quality, scientific rigor and innovation.
What you’ll be doing:
- Conduct research on driving behavior related topics, such as motion prediction and planning, agent simulation, scenario generation, Vision-Language-Action model(VLA), etc.
- Work with large-scale internal realworld driving datasets to demonstrate the effectiveness of your research
- Collaborate with different teams to deploy your research results into the autonomous vehicles and test it onroad.
- Publish the research results in papers and patents
What we are looking for:
- Enrolled in a PhD program in Computer Science, Electrical Engineering, Robotics or similar technical field of study
- Strong Machine Learning research background with publications in any of the top-tier conferences(RSS, ICRA, CoRL, CVPR, ICRL, ICML, NeurIPS, etc.)
- Proficiency in Python coding and PyTorch or other commonly-used deep learning frameworks
- One-team mindset and effective collaboration with other researchers and engineers
- Strong communication and interpersonal skills
- Previous experience in autonomous driving is preferred
Note: This will be a hybrid onsite internship position in Boston or Pittsburgh. We will accept resumes on a rolling basis until the role is filled. Compensation will be based on location and degree level.
Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more.
Our journey is always people first.
We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.
Higher purpose, greater impact.
We’re creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it’s not only good for our business, it’s the right thing to do.
Scale up, not starting up.
Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We’re driven to scale; we’re moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.
Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.
Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.
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Навыки
- Python
- PyTorch
- Machine Learning
- Deep Learning
- Motion Prediction
- Autonomous Driving
- Computer Vision
- Robotics
Возможные вопросы на собеседовании
Проверка глубины теоретических знаний и актуальности исследований кандидата.
Расскажите о вашей самой значимой публикации: какую проблему вы решали и в чем заключалась научная новизна?
Оценка практических навыков работы с современными архитектурами, упомянутыми в вакансии.
Как бы вы подошли к интеграции Vision-Language-Action (VLA) моделей в систему планирования траектории беспилотника?
Проверка умения работать со специфическими данными Motional.
Какие основные сложности вы видите при обучении моделей на датасетах nuScenes или nuPlan и как их можно нивелировать?
Оценка навыков программирования и оптимизации.
Опишите ваш опыт оптимизации пайплайнов обучения в PyTorch для работы с терабайтами данных с сенсоров.
Проверка навыков командной работы в междисциплинарной среде.
Опишите случай, когда вам приходилось адаптировать свои теоретические исследования под жесткие инженерные ограничения реальной системы.
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