We are looking for a passionate and motivated researcher with a solid track record of solving challenging problems, advancing state-of-the-art, and demonstrated passion for ground-breaking research that could be scaled to production environment with an emphasis on the intersection of AI and Safety.
Your responsibilities:
· Create new techniques to make AI models more interpretable, unbiased, transparent and aligned with human values for real-world scenarios.
· Create new techniques to ensure consistent alignment between user-centric explanations and intrinsic model behavior.
· Reverse-engineer on neural networks to understand internal workings of AI models rather than treating them as ‘black boxes’.
· Develop data attribution methods to quantify the influence of specific data points (text and image) on a model’s prediction and implement solution.
· Implement and integrate AI explainbility techniques and tools.
· Build rigorous benchmarks and datasets to measure the quality of explanations, model transparency, and effectiveness of treatments.
· Communicate insights to stakeholders.
Requirements:
· Ph.D. in Computer Science, Deep Learning, Machine Learning, Mathematics or other related fields.
· Focused on research in the AI field with good track records and high motivation in Explainable AI and Safety domain.
· Strong proficiency in Large Language Models (LLMs), neural networks, and computer vision architectures.
· Strong background in Python, Java, or C++, with deep knowledge of ML frameworks such as PyTorch, TensorFlow.
· Successful experience in AI alignment to human values and expectations, model robustness improvement, controlled and continual learning, neural network interpretability and editing techniques is highly valued.
· Pioneering novel methods and neural networks that revolutionized machine learning or the AI field, or revolutionized the industry, is a big bonus.
· Strong publication record in top conferences (i.e. NeurIPS/ICLR/ICML/ AAAI/ACL/CVPR/ICCV/EMNLP/NAACL).
· Candidates with ICPC, IOI/IMO, IOAI and other international competition in computer science, machine learning, and AI, etc. are highly preferred.
· Good teamwork, enjoy working with multi 8209;culture teams, passionate in challenging the status quo.
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