Research Scientist
On-sitePresidio, Texas, United States
Job Summary
Pioneer novel neural architectures, loss functions, and multimodal integration techniques to teach foundation models how to evaluate consumer products like an expert appraiser. Lead the deep fine-tuning, adaptation, and structural optimization of state-of-the-art Vision-Language Models for complex tasks including generating context-aware captions, predicting market price points, and estimating subjective aesthetic quality. Develop mathematical foundations to extract nuanced signals from product images and guide the creation, curation, and algorithmic augmentation of specialized multimodal datasets. Invent rigorous evaluation frameworks and custom metrics to measure performance on abstract tasks where standard benchmarks do not exist. Collaborate with engineering teams to translate proprietary research into scalable, production-ready systems.
Required Qualifications
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or a strictly related field
- A strong track record of advancing the state-of-the-art, evidenced by first-author publications in top-tier AI, CV, or NLP venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ACL)
- Deep theoretical and practical understanding of Vision-Language Models, multimodal architectures, and modern transformer-based computer vision
- Expert-level proficiency in Python and deep learning frameworks (specifically PyTorch), with the ability to write optimized training loops when necessary
- A proven track record of formulating highly ambiguous, real-world visual problems into rigorous, solvable machine learning tasks
Desired Qualifications
- Prior industrial experience as a Research Scientist or Machine Learning Engineer, specifically involving the deployment of deep learning models to large-scale production environments
- Previous experience applying machine learning to product imagery, retail technology, or computational aesthetics
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.