Postdoctoral Researcher, Monetization
Meta

Job Info

Meta is seeking a Postdoctoral Researcher to join Monetization Ranking & AI Foundations where we strive to serve the best personalized ads to people by maximizing their personal utility and advertiser value. We are committed to making fundamental advances in Artificial Intelligence and Machine Learning technologies that can be applied to all aspects of Monetization, including but not limited to, ranking, retrieval, supply, model architecture, representation learning, optimization, and generally a deep understanding of the users, ads, and any signals and contents related to their interactions. As a Postdoctoral Researcher, you will closely collaborate with Researchers and Engineers within the organization and across the company (e.g., FAIR), push the boundaries of state-of-the-art research in AI and ML, share the latest findings through top-tier publications and open source, and integrate innovations at an unprecedented scale.

Postdoctoral Researcher, Monetization Responsibilities:

• Conduct state-of-the-art research to advance the science and technology of Machine Learning and Artificial Intelligence.
• Develop novel algorithms and corresponding systems, leveraging various AI and ML techniques.
• Produce and publish state-of-the-art research findings at relevant conferences to influence the progress of AI/Machine Learning.
• Collaborate closely with cross-functional partners across diverse disciplines and contribute towards Meta's research product development.

Minimum Qualifications:

• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
• Experience with Deep Learning frameworks such as Pytorch or Tensorflow.
• Experience with Python, C++, C, Java, or other related languages.
• Experience with research and building systems based on Machine Learning and/or Deep Learning methods.
• Experience in solving modeling problems using AI or Machine Learning methodologies.

Preferred Qualifications:

• Proven track record of achieving significant research results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, KDD, IJCAI, CVPR, ICCV, ACL, NAACL, ICASSP, or similar.
• Research experience in reinforcement learning, causal learning, graph learning, graph neural networks, sequence modeling, next-generation and large-scale model architectures, ML systems and hardware-software co-design, data-related in general (e.g., semi/self/un-supervised learning, generative techniques, content understanding, LLM, etc.), or similar.
• Extensive experience in designing and developing algorithms using popular Machine Learning frameworks (e.g PyTorch) in Python.
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources for large-scale training.
• Experience working and communicating cross functionally in a team environment.
• Experience in solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward.

About Meta: