Meta is looking to improve user acquisition and growth relevance by developing cutting-edge deep learning algorithms and machine learning models for recommendation systems.
Requirements
- Machine Learning Framework(s): PyTorch and Tensorflow
- Proven track record in research project/internship experience involved developing and implementing large scale machine learning models
- Machine learning, natural language processing, data mining, large language models (LLMs)
- State-of-the-art deep learning technologies, particularly in applying causal inference, model debiasing to enhance model accuracy and fairness
- Data pipeline technologies: Spark and Hadoop
- Developing and debugging in C, C++, C-Sharp and Java
- Scripting languages: Python, PHP, or shell scripts
Responsibilities
- Innovate and implement cutting-edge deep learning algorithms and machine learning models for recommendation systems.
- Directly influence user acquisition and growth relevance by uncovering valuable insights from data.
- Develop and implement large scale machine learning models.
- Build recommendation systems using LLM and other state-of-the-art deep learning techniques.
- Improve the user experience through cross-functional collaboration with product team.
- Develop and implement techniques such as model debiasing, signal development, embedding development, responsiveness, and recommendation quality.
- Integrate with Family of Apps and leverage state of the art AI technology.
Other
- Bachelor’s degree in Computer Science, Computer Software, Computer Engineering, Statistics, Machine Learning, Applied Sciences, Mathematics, Physics, or related field
- Two years of work experience in the job offered or in a computer-related occupation
- Two years of experience in the required technical skills
- Must be eligible to work in the United States
