As an Artificial Intelligence Research Scientist, you will join a team of researchers focused on improving the reliability of foundation models. This research-oriented role involves leading cutting-edge projects to solve complex analytical problems by creating and leveraging innovative machine learning and NLP techniques. You will design and conduct experiments to evaluate algorithm properties and their impact on user experiences, while also integrating research algorithms into usable systems to ensure optimal performance. You will utilize frameworks such as Tensorflow, Caffe, PyTorch, or Theano to drive project success. Additionally, you will communicate your findings to the technical community through publications in top-tier journals and conferences like NIPS, CVPR, and ICML. This role addresses the technical challenge of developing dependable, high-performing AI technologies.
Python
PyTorch
TensorFlow
Deep Learning
Reinforcement Learning
LLMs
Probabilistic Modeling
Causal Inference
Multi-Agent Systems
Neuro-symbolic AI
Time-series Forecasting
Simulation-based Planning
Model Training
Data Science
Machine Learning
Foundation Models
Multimodal Learning
Computer Vision
Generative AI
Deep Learning
Medical Imaging
Vision-Language Models
Model Distillation
Few-Shot Learning
Zero-Shot Learning
Self-Supervised Learning
Transfer Learning
Representation Learning
Model Compression
Parameter-Efficient Adaptation
Electronic Health Records
Medical AI