Research Scientist Intern, Reinforcement Learning
il y a 3 jours
**Research Scientist Intern, Reinforcement Learning (PhD) 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.
- Publish research results and contribute to research that can be applied to Meta product development.
**Minimum Qualifications**:
- 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.
**Preferred Qualifications**:
- 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.
**About Meta**: Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules 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 benefits. Learn more about benefits at Meta.
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