Research Engineer - Conversational AI - Reality Labs

Reality Labs is seeking a Research Engineer to join our Large Language Model (LLM) Research team for the device driven AI Assistant effort. We conduct focused research and engineering to build state-of-the-art LLMs to fit on-device and on-server use cases. We are looking for strong research engineers who have a background in generative AI and NLP, with experience in areas like language model evaluation;

data processing for pre-training and fine-tuning; responsible LLMs; LLM alignment; reinforcement learning for language model tuning; efficient training and inference; and/or multilingual and multimodal modeling. We collaborate closely with Meta GenAI and FAIR orgs to produce SOTA research and results.

• Design methods, tools, and infrastructure to push forward the state of the art in large language models.
• Define research goals informed by practical engineering concerns.
• Contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results.
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
• Work with a large and globally distributed team.
• Contribute to publications and open-sourcing efforts.

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Research experience in machine learning, deep learning, and/or natural language processing.
• Experience with developing machine learning models at scale from inception to business impact.
• Programming experience in Python and hands-on experience with frameworks such as PyTorch.
• Exposure to architectural patterns of large scale software applications.

• Master's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• A PhD in AI, computer science, data science, or related technical fields.
• Direct experience in generative AI and LLM research.
• First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).