• 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

We are looking for strong 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

• 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

Meta participates in the E-Verify program in certain locations, as required by law

$88.46/hour to $257,000/year + bonus + equity + benefits