Responsibilities
- Develop and implement large-scale model architectures, leveraging model scaling and transfer learning techniques
- Prioritize training scalability and signal scaling to optimize model performance, efficiency, and reliability
- Develop and apply NextGen sequence learning techniques to drive advancements in natural language processing and understanding
- Design and implement generative modeling solutions for data augmentation
- Research and develop graph-aware large language models
- Develop and deploy AutoML pipelines
- Apply Reinforcement Learning (RL) techniques, including long-term value optimization, RLHF, and RL4Reason
- Use causal learning to identify and understand the cause and effect of relationships across data
- Collaborate with cross-functional teams to design and optimize ML systems, leveraging expertise in hardware-software co-design, including quantization, compression, and resource-efficient AI, to drive performance improvements and efficiency gains
- Develop and implement innovative solutions for data-related challenges, utilizing knowledge of semi/self-supervised learning, generative techniques, sampling, debiasing, domain adaptation, continual learning, data augmentation, cold-start, content understanding, and large language models
Minimum Qualifications
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Has obtained a PhD in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, or relevant technical field
- Experience holding an industry, faculty, or government researcher position
- Research experience in natural language processing, large language modeling, deep learning, reinforcement learning, recommendations, ranking, search, or related areas
- Publications in machine learning, artificial intelligence, or related field
- Programming experience in Python and hands-on experience with frameworks such as PyTorch
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment
Preferred Qualifications
- Experience taking ideas from research to production
- First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward
$122,000/year to $181,000/year + bonus + equity + benefits
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