Research Scientist in Reinforcement Learning
il y a 3 semaines
Meta is on the lookout for a Research Scientist specializing in reinforcement learning to contribute to our esteemed research division, FAIR. We are interested in candidates who can collaborate with our reinforcement learning experts to develop innovative algorithms based on robust principles, aimed at effectively addressing intricate real-world challenges. Our research encompasses various facets of reinforcement learning, with a specific emphasis on unsupervised and self-supervised RL to create behavioral foundation models. The ideal candidate will possess a strong foundation in machine learning and reinforcement learning, along with experience in constructing and overseeing complex reinforcement learning systems at scale.
Research Scientist in Reinforcement Learning (PhD) - Responsibilities:- Work closely with the research supervisor and team to create novel behavioral foundation models that empower agents to tackle a diverse array of challenges with minimal retraining.
- Develop and implement algorithms, train cutting-edge models on extensive datasets, and assess their effectiveness.
- Disseminate research findings through publications, libraries, models, or demonstrations.
- Currently pursuing or in the process of completing a PhD or postdoctoral assignment in Computer Science or a related field. Degree completion is required prior to joining Meta.
- Proficient programming skills.
- Strong understanding of the principles of reinforcement learning.
- Experience in managing complex machine learning codebases at scale.
- Proven ability to collaborate within a research team to address complex issues.
- Must secure work authorization in the country of employment at the time of hire and maintain ongoing work authorization throughout employment.
- First-authored publications in peer-reviewed conferences (ICML, ICLR, NeurIPS, CoRL, ICRA, AAAI, AAMAS, or similar).
- Demonstrated machine learning experience through internships, open-source contributions, or data science competitions.
- Experience in developing high-performance implementations using deep learning frameworks (such as PyTorch, TensorFlow), C, C++, or Python.
- Proven track record of solving complex problems and evaluating alternative solutions, trade-offs, and diverse perspectives to determine a viable path forward.
- Experience in cross-functional teamwork and effective communication.
Meta is dedicated to creating technologies that facilitate connections, foster communities, and support business growth. Since the launch of Facebook in 2004, we have transformed the way individuals connect. Platforms like Messenger, Instagram, and WhatsApp have empowered billions globally. Currently, Meta is advancing beyond traditional 2D interfaces towards immersive experiences such as augmented and virtual reality, aiming to shape the next evolution in social technology. Those who choose to build their careers with us at Meta contribute to a future that transcends the limitations of digital connectivity—beyond screens, distances, and even the laws of physics.
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity, or sales incentives, if applicable. In addition to base compensation, Meta offers a comprehensive benefits package. Learn more about benefits at Meta.
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