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Founding AI Engineer, Computer Vision

San Francisco, USオンサイト契約社員フルタイム

2026年9月25日に掲載

市場ベンチマーク: 中央値€108,750

USの求人24件に基づく

この求人はENで掲載されています

Founding AI Engineer, computer vision

Seed physical-AI company

The company is building a wearable AI copilot for industrial field technicians, running on real hardware against real customer workflows. It is seed-funded and building a four-person founding engineering team in the Bay Area.


SF Bay Area (Burlingame)

On-site

Mid-level

$180k–$240k base + 0.25% to 0.75% Equity



The role

Own the AI core: agentic VLM, multimodal visual reasoning, evals, model orchestration, running on real hardware against real customer workflows. Priority is visual AI, including detection, segmentation, reasoning over image and video, VLMs and VLAs, over general agentic AI. Applied agentic work plus real evals discipline.



What they are looking for


1. Shipped multimodal or CV systems to production and owned the model layer end to end

2. Applied agentic work plus real evals discipline: ground-truth, trajectory and regression harnesses

3. 1 to 5 years, bachelor’s roughly 2018 or later

4. Bay Area, fully in person



Good to know


  1. The focus is visual AI, including detection, segmentation, VLMs and VLAs, rather than general agentic AI.

  2. Visa sponsorship is available for candidates already in the US through O-1, TN, E-3, H-1B1, H-1B transfers, OPT and STEM OPT. The company does not sponsor petitions from abroad.


How they interview

  1. Intro call with a co-founder

  2. Technical stage with both co-founders

  3. On-site with the team

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職種スナップショット

職種

フルタイム

Email

support@workfully.com

必要なスキル

Computer Vision (object detection & segmentation)Vision-Language Models (VLMs) & Vision-Language Agents (VLAs)Multimodal visual reasoning over images and videoProductionizing ML/CV models and owning the model layer end-to-endModel orchestration and servingEvaluation design and test harnesses (ground-truth, trajectory, regression)Agentic AI system development (agentic VLMs)Edge/on-device deployment and optimization for real hardwareVideo understanding and real-time video processingMLOps/model lifecycle management and monitoringData labeling and ground-truthing processesSystems integration with hardware and embedded software interfaces

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