Founding AI Engineer – Computer Vision & Multimodal Models
About The Position
The Founding AI Engineer will build and deploy vision-language systems that reason over images and video in real customer environments. The role owns critical parts of the AI layer at an early-stage technology company developing AI systems for real-world industrial environments. It combines applied AI, computer vision, evaluation systems, and production engineering, with an emphasis on multimodal visual intelligence for hardware-constrained environments and complex physical workflows. The position is fully in person in the San Francisco Bay Area. The initial work location is Burlingame, with the team expected to transition to a San Francisco office. Candidates must be able to work in the United States. Certain visa sponsorship, transfer, or change-of-status scenarios may be supported for candidates already in the United States; new petitions requiring processing from abroad are not supported at this time.
Requirements
- 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.
- Must be able to work in the United States.
Nice To Haves
- Experience in robotics, autonomous systems, drones, wearables, real-time video, edge computing, or adjacent physical-world AI domains.
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, vision-language models, 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.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
No Education Listed
