Meta AR/VR Job | Research Scientist Intern, Reinforcement Learning for Embodied AI (PhD)
Job（岗位）: Research Scientist Intern, Reinforcement Learning for Embodied AI (PhD)
Type（岗位类型）: Artificial Intelligence | Computer Vision, Engineering, Machine Learning, Research
Citys（岗位城市）: Redmond, WA
Date（发布日期）: Before 2021-12-14
Summary（岗位介绍）
Reality Labs Research is looking for an intern to help us develop the next generation assistance systems that guide the users in contextual and adaptive future AR/VR systems. In particular, we are seeking candidates who have experience with embodied AI, reinforcement learning, deep reinforcement learning (RL/DRL), robotics, neuro-symbolic approaches, and planning under uncertainty, along with experience in machine/deep learning methods to devise learning algorithms that make high fidelity machine guidance for day-to-day tasks a reality.
Qualifications（岗位要求）
Currently has, or is in the process of obtaining, a PhD in machine learning, artificial intelligence (AI), robotics, algorithms, computational mathematics or a related field.
Excellent research and communication skills involving defining problems, exploring solutions, and analyzing and presenting ideas and results.
3+ years of experience in Python.
1-2 years of experience with implementing and training/testing AI/ML models using Pytorch or Tensorflow.
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
Description（岗位职责）
Plan and execute cutting-edge research on developing novel embodied AI algorithms that can learn AR assistance policies in long-tailed and complex interaction tasks prevalent in everyday life.
Leverage state-of-the-art (SOTA) embodied AI simulators and RL/DRL, neuro-symbolic, AI planning, robotics or stochastic programming methods to train and test policy models.
Work towards taking on big problems and deliver clear, compelling, and creative solutions to solve them at scale. This is an exciting opportunity to conduct SOTA research while collaborating with other researchers, and engineers to develop, prototype, and test different AI/ML models at-scale for real-world interactive applications.
Successful internships will also lead to publishable outcomes in top-tier journals or at leading international conferences.
Additional Requirements（额外要求）
Published at least one paper in a top conference (CVPR, ICCV, ICML, NeurIPS, IJCAI, AAAI, AAMAS, EECV, ICLR, ICRA, IROS, RSS, CoRL etc).
Experience with simulation platforms (eg. OpenAI Gym, Habitat, AI2Thor etc).
Proficiency in implementing reinforcement learning and/or planning algorithms on a large-scale.
Expertise in topics such as neuro-symbolic approaches, stochastic and belief space planning, decision making under uncertainty.
Intent to return to degree-program after the completion of the internship/co-op.
