Founding AI Engineer - Multimodal Vision at the Edge

MaxIT Consulting - Max Corporate Group; San Francisco (CA); Sur place; USD 180 000 - 230 000; Plein temps

Résumé du poste

MaxIT Consulting - Max Corporate Group in the San Francisco Bay Area is seeking a Founding Computer Vision Engineer to lead multimodal AI and vision-language model deployment in real-world industrial settings.

You will own end-to-end CV/vision-language systems, drive edge deployment strategies for hardware-constrained environments, and collaborate with robotics, data, and software teams to ship production-ready solutions.

Qualifications

• 1–5 years of relevant professional experience.
• Hands-on experience shipping computer vision, multimodal, or vision-language systems to production.
• Strong practical understanding of visual AI applied to images and/or video.
• Experience owning technical systems end to end rather than research prototypes.
• Comfort operating in real-time, edge, hardware-constrained, or connectivity-constrained environments.

Responsabilités

• Build and deploy agentic vision-language systems for real-world industrial workflows.
• Develop multimodal reasoning capabilities across images and video.
• Work with detection, segmentation, visual reasoning, VLMs, and related applied computer vision techniques.
• Own model orchestration and production deployment across hardware-constrained environments.
• Design and maintain evaluation systems including ground-truth datasets, trajectory evaluation, and regression testing.
• Iterate on production models based on real-world usage and measurable system performance.

Connaissances

Computer vision

Edge computing

Software engineering

Production deployment

Outils

Python

PyTorch

TensorFlow

Description du poste

MaxIT Consulting - Max Corporate Group in the San Francisco Bay Area is seeking a Founding Computer Vision Engineer to lead multimodal AI and vision-language model deployment in real-world industrial settings.

You will own end-to-end CV/vision-language systems, drive edge deployment strategies for hardware-constrained environments, and collaborate with robotics, data, and software teams to ship production-ready solutions.