**Summary:** Meta is seeking Research Engineers to join Fundamental AI Research (FAIR). We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in solving systems challenges to sustainably accelerate our reach to human-level intelligence. Candidates will have an opportunity to make fundamental advances in systems and apply their ideas at an unprecedented scale. The mission of Meta FAIR's CodeGen research is to advance the state of AI through open science innovations. We explore, design, and conduct fundamental research on Code Generation and Computational World Modeling at scale with usability, efficiency, and sustainability as design principles. **Required Skills:** Research Engineer, CodeGen - FAIR Responsibilities: 1. Perform research to advance the science and technology of intelligent machines. Specifically, Contribute research that leads to innovations in Code Generation, Code World Modeling, Agentic Code Generation, Math Reasoning, etc. 2. Perform research that enables learning the code data (images, video, text, code, audio, and other modalities). 3. Devise better data-driven models of AI code generation systems. 4. Work towards long-term research goals, while identifying immediate milestones. 5. Influence progress of relevant research communities by producing publications. 6. Open source high quality code and produce reproducible research. 7. Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results. **Minimum Qualifications:** Minimum Qualifications: 8. Master's degree in Computer Science, Computer Engineering, a relevant technical field, and 2+ years of equivalent domain-specific industry experience. 9. Research background in machine learning, artificial intelligence, computational statistics, applied mathematics, or related areas. 10. Experience with Python, C++, C, Rust or other related languages and with PyTorch framework. 11. Experience with training machine learning systems, Large Language Models optimization with specific focus on code / math data. 12. Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward. 13. Experience working and communicating cross functionally in a team environment. 14. Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment. **Preferred Qualifications:** Preferred Qualifications: 15. PhD in the field of Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. 16. Proven track record of achieving significant results and publications as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as NeurIPS, ICML, ICLR, ACL, COLM, Interspeech, or similar. 17. Demonstrated research and software engineering experience via work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub). **Industry:** Internet