Edge Vision & Multimodal AI Engineer

MaxIT Consulting - Max Corporate Group; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

MaxIT Consulting - Max Corporate Group in the San Francisco Bay Area is seeking a Multimodal Intelligence Systems Engineer to own critical AI components, deploying vision-language systems for real-world industrial workflows and production environments. The role emphasizes practical delivery, end-to-end ownership, and on-site work in Burlingame transitioning to San Francisco.

The ideal candidate ships real systems, works with vision-language techniques, and thrives in hardware-constrained,

Qualifications

• Approximately 1 to 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 working exclusively on research prototypes.
• Comfort operating in real-time, edge, hardware-constrained, or connectivity-constrained environments.
• Strong software engineering fundamentals and a high level of technical ownership.

Responsibilities

• 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.

Skills

Computer vision

Multimodal systems

Edge computing

Production deployment

Software engineering

Real-time systems

Job description

MaxIT Consulting - Max Corporate Group in the San Francisco Bay Area is seeking a Multimodal Intelligence Systems Engineer to own critical AI components, deploying vision-language systems for real-world industrial workflows and production environments. The role emphasizes practical delivery, end-to-end ownership, and on-site work in Burlingame transitioning to San Francisco.

The ideal candidate ships real systems, works with vision-language techniques, and thrives in hardware-constrained,