AI Research Engineer, Computer Vision & VLMs

What you'll do

• Develop and evaluate models for scene understanding, object detection and tracking, activity recognition, and video-event reasoning.
• Build datasets, annotation workflows, experiments, and benchmarks; analyze failures and improve model robustness.
• Partner with product and engineering teams to deploy efficient, monitored inference systems and translate research into product capabilities.

What they ask for

• 3+ years of research or applied development in computer vision, multimodal learning, or a closely related field; relevant graduate research counts.
• Demonstrated research track record in computer vision or vision-language modeling.
• Hands-on experience training, fine-tuning, or adapting computer vision models and developing or evaluating VLMs beyond basic API integration.
• Strong Python skills and experience with PyTorch or an equivalent deep learning framework.

Nice to have

• PhD or research-focused master’s degree in a related field, or equivalent research experience; relevant industry experience in autonomous driving, robotics, embodied AI, or physical-world perception.
• Publications at listed venues; experience in monocular video perception, spatial understanding, long-video reasoning, noisy labels, or shipping real-time vision models.

Tools

Python, PyTorch, CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML

AI focus

Research, train, fine-tune, evaluate, and deploy computer vision and VLM systems for restaurant scene and video understanding, including spatiotemporal reasoning, visual grounding, tracking, and robust inference.