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We are seeking an Applied Research Scientist to join our Content Understanding team within Modern Recommendation Systems (MRS). The team is pushing the frontiers of multimodal perception, addressing fundamental research challenges, and delivering high-performing, scalable models from prototype to production. As a Research Scientist, you will help us develop innovative models and algorithms and apply them to large-scale production Computer Vision tasks. Responsibilities include leading and collaborating on research that advances the state of the art, training production-quality single- and multi-modal content understanding models on billions of data samples, integrating the models into downstream applications, and working with and creating large datasets and benchmarks.
Applied Research Scientist, Computer Vision - MRS Responsibilities
- Develop algorithms based on state-of-the-art machine learning and neural network methodologies.
- Conduct research that enables learning the semantics of data (images, video, and their relationship to text, audio, speech and other modalities).
- Carefully evaluate the performance of proposed models.
- Collaborate on bringing the models from prototyping to production within a globally-based team.
- Initiate and lead research projects within a team and collaborate with cross-functional partners.
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- A PhD degree in AI, computer science, data science, or related technical fields.
- Research background in Computer Vision, Deep Learning, Machine Learning, or related field(s).
- 2+ years of Industry or academic research experience on cutting edge computer vision technologies
- Experience in developing and debugging in Python or similar programming languages.
- Experience in deep learning frameworks such as PyTorch or TensorFlow.
- Experience in theoretical and empirical research and in addressing research problems.
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, or first-authored publications at conferences such as CVPR, ECCV, ICCV, ICML, NeurIPS, SIGGRAPH, or similar.
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
- Experience working and communicating cross functionally in a team environment.
- Experience in leading, planning and coordinating long-term research-to-production projects.
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