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3 дня назад

Robotics Intern (Post-Training and Continual Learning)

45 - 65$
Формат работы
hybrid
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Robotics Intern (Post-Training and Continual Learning) (reinforcement learning/robotics): Developing methods that adapt pretrained generalist robot policies to new tasks, environments, and robotic systems with an accent on offline-to-online reinforcement learning, imitation learning, simulation, and world models. Focus on designing rigorous simulation and real-robot experiments, analyzing results, and building data-efficient policy adaptation methods for reliable downstream performance.

Location: Los Altos, California, United States; hybrid, in-office role

Salary: $45–$65 per hour for California-based roles

Company

hirify.global develops tools and capabilities in AI, robotics, driving, and material sciences to improve the quality of human life.

What you will do

  • Develop post-training methods that adapt pretrained generalist robot policies to new tasks, environments, and robotic systems.
  • Design and conduct rigorous experiments in simulation and, where appropriate, on real robotic systems.
  • Analyze results, communicate findings, and contribute to research publications and internal technical reports.

Requirements

  • Currently pursuing a Ph.D. in Computer Science, Machine Learning, Robotics, or a related field.
  • Research experience in robot learning, reinforcement learning, imitation learning, generative modeling, world models, or a related area.
  • Interest in open research problems involving large-scale machine learning grounded in physical systems.
  • Proficiency in Python and a deep-learning framework such as PyTorch.
  • Ability to collaborate effectively with researchers and engineers and communicate research findings clearly.

Nice to have

  • Experience with pretrained generalist policies, foundation models, or large-scale robot-learning systems.
  • Familiarity with offline or online reinforcement learning, DAgger, interactive learning, or human-in-the-loop methods.
  • Experience with simulation, sim-to-real transfer, policy distillation, or robotic manipulation.
  • Experience with learned world models, model-based reinforcement learning, or planning.
  • Publication record or interest in publishing at leading venues such as CoRL, NeurIPS, ICLR, ICML, RSS, ICRA, IROS, or related conferences and journals.
  • Interest in translating fundamental research into reliable methods evaluated on real robotic systems and practical downstream tasks.

Culture & Benefits

  • Paid 12-week internship.
  • Hybrid, in-office work arrangement.
  • Medical, dental, and vision insurance.
  • Paid time off, including holiday pay and sick time.

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