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Meta Applied Research Scientist, Computer Vision - MRS in New York, New York

Summary:

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.

Required Skills:

Applied Research Scientist, Computer Vision - MRS Responsibilities:

  1. Develop algorithms based on state-of-the-art machine learning and neural network methodologies.

  2. Conduct research that enables learning the semantics of data (images, video, and their relationship to text, audio, speech and other modalities).

  3. Carefully evaluate the performance of proposed models.

  4. Collaborate on bringing the models from prototyping to production within a globally-based team.

  5. Initiate and lead research projects within a team and collaborate with cross-functional partners.

Minimum Qualifications:

Minimum Qualifications:

  1. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

  2. A PhD degree in AI, computer science, data science, or related technical fields.

  3. Research background in Computer Vision, Deep Learning, Machine Learning, or related field(s).

  4. 2+ years of Industry or academic research experience on cutting edge computer vision technologies

  5. Experience in developing and debugging in Python or similar programming languages.

  6. Experience in deep learning frameworks such as PyTorch or TensorFlow.

  7. Experience in theoretical and empirical research and in addressing research problems.

  8. Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications:

Preferred Qualifications:

  1. 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.

  2. Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

  3. Experience working and communicating cross functionally in a team environment.

  4. Experience in leading, planning and coordinating long-term research-to-production projects.

Public Compensation:

$143,000/year to $208,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@fb.com.

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