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Research Scientist Intern, Reinforcement Learning
il y a 2 semaines
Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.
Responsibilities
- Develop novel state-of-the-art reinforcement learning algorithms and corresponding systems, leveraging various deep learning techniques.
- Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.
- Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence.
- Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
- Contribute to research that can be applied to Meta product development.
- Currently has or is in the process of obtaining a PhD degree in Machine Learning, Artificial Intelligence, Computer Science, Reinforcement Learning, Mathematics, or relevant technical field
- Solid background on the foundations of reinforcement learning
- Ability to implement and run reinforcement learning algorithms in complex environments
- Experience collaborating within a team to solve complex problems
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
- Experience with Python, C++, C, Java or other related languages
- Experience with deep learning frameworks such as Pytorch or JAX
- Experience building systems based on machine learning and/or deep learning methods
- Research experience with algorithms for sequential decision-making, e.g., planning, reinforcement learning, or similar
- Intent to return to a degree program after the completion of the internship/co-op
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICLR, ICML, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV,, ICASSP, or similar
- Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches
- ML/ AI research and/ or work experience in deep reinforcement learning
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
- Experience working and communicating cross functionally in a team environment
