AI Research Scientist, VLLM (Vision Large Language Models) - Generative AI

**Summary:** From making valuable connections between people and businesses to building premium services that deliver high-value experiences, the Monetization organization at Meta empowers people and businesses to succeed in the global economy. As Meta focuses on building the next evolution of social experiences, the Monetization team plays a crucial role in shaping the communication pathways and financial tools that all sized businesses need to thrive in the new digital economic environment. As a Machine Learning Research Scientist on the Monetization team at Meta, you can help build ML/AI technologies that can effectively connect users with businesses You’ll help develop solutions that power next-generation, large-scale platforms and AI innovations to power the Ads-ranking for Meta-scale across all the Meta surfaces. **Required Skills:** AI Research Scientist, VLLM (Vision Large Language Models) - Generative AI Responsibilities: 1. Develop highly scalable classifiers and tools leveraging Machine Learning, data regression, and rules-based models 2. Suggest, collect, and synthesize requirements to create an effective feature roadmap 3. Adapt standard Machine Learning methods to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU) 4. Lead and contribute to cutting-edge research that results in industry-leading tech demos and/or publications 5. Collaborate closely with cross-functional partners and contribute to Meta's research product development **Minimum Qualifications:** Minimum Qualifications: 6. Experience in Deep Learning algorithms and techniques, e.g., convolutional neural networks (CNN), transformers, quantization, data-efficient learning, or similar 7. 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: 8. Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub) 9. Experience in data efficient learning, domain adaptation, semi-supervised learning, etc 10. Experience working and communicating cross-functionally in a team environment 11. 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, ICML, ICLR, AAAI, or similar 12. Exposure to architectural patterns of large-scale software applications 13. Experience in manipulating and analyzing complex, high-volume, high-dimensionality data from various sources 14. Experience solving complex problems and comparing alternative solutions, trade-offs, and varied points of view to determine a path forward **Public Compensation:** $154,000/year to $217,000/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@meta.com.