Research Engineer, Language - Content and User Understanding Team
Job Description
Meta is seeking a Research Engineer to join content and user understanding team, with a focus of Large Language Model (LLM). We conduct focused research and engineering to build state-of-the-art LLMs. As a key driver of Meta's app growth, we're dedicated use LLM-powered world knowledge to deliver user experiences across Facebook, Instagram, Threads, and more. We are looking for engineers with a background in generative AI and NLP. Experience in areas like language model evaluation, data processing for pre-training and fine-tuning, LLM alignment, reinforcement learning for language model tuning, efficient training and inference, and/or multimodal modeling is desired.
Locations
- Menlo Park, CA, USA
- Seattle, WA, USA
- New York, NY, USA
Salary
177,008 - 251,000 USD / yearly
Skills Required
- Pythonintermediate (Programming)
- PyTorchintermediate (Framework)
- Machine Learningadvanced (AI)
- Natural Language Processingadvanced (AI)
- Generative AIadvanced (AI)
- Large Language Modelsadvanced (AI)
Required Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience (degree in Computer Science)
- Research experience in machine learning, deep learning, and/or natural language processing (experience in Machine Learning)
- Experience with developing machine learning models at scale from inception to business impact (experience in Machine Learning)
- Programming experience in Python and hands-on experience with frameworks such as PyTorch (experience in Programming)
- Understanding of architectural patterns of large scale software applications (experience in Software Engineering)
Preferred Qualifications
- First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL) (experience in Research)
- Master's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience (degree in Computer Science)
- A PhD in AI, computer science, data science, or related technical fields (degree in AI)
- Direct experience in generative AI and LLM research (experience in Generative AI)
Responsibilities
- Build Multi-Modal LLM backbones
- Prepare human-labeled or auto-generated data for pre-training and fine-tuning
- Fine-tune/RLHF for downstream content understanding and user understanding tasks
- Model evaluation with human labeling or auto judge
Benefits
- compensation: Bonus + equity + benefits
