Skill
Transfer Learning
Data Science, Analytics and AI/ML
Transfer learning is a machine learning technique in which a model trained on one task or dataset is reused, often with fine-tuning, as the starting point for a related task. It allows practitioners to achieve strong performance with less data and compute by leveraging pretrained models like BERT or ResNet. It's widely used by data scientists and ML engineers in computer vision and natural language processing applications.
Open roles requiring Transfer Learning (1)
AI/ML Scientist, Planetary Science
Relativity Space
Full-time · Long Beach, CA · $115,000 – $173,000
This role applies machine learning to unlock discoveries from Mars missions, focusing on atmospheric modeling, multi-modal data fusion, and autonomous science decision-making on spacecraft. It suits researchers who want to bridge cutting-edge AI methods with planetary science problems in a lean, high-ownership environment.
Listed on Relativity Space’s careers site · Apply there ↗
Roles that use Transfer Learning
Related skills
Curated neighbors in the taxonomy, whether or not employers ask for them together.