
DeepHow is an award-winning AI-powered video companion for the manufacturing frontline. DeepHow improves worker and knowledge retention and drives operational efficiency, quality, and safety. Our…

DeepHow is an award-winning AI-powered video companion for the manufacturing frontline. DeepHow improves worker and knowledge retention and drives operational efficiency, quality, and safety. Our…
What they do: AI-powered video-based operational knowledge platform for manufacturing and other industrial sectors
Founded: 2018
Reported reach: Deployed across 1,500+ sites in 28+ countries
Recent financing: Series A (Dec 28, 2022) with investors including Owl Ventures and Qualcomm Ventures
Knowledge capture and onboarding, frontline training, skills management, and operational verification in manufacturing, energy, pharma, and service industries.
2018
Software Development
Crunchbase lists Owl Ventures as lead for the Dec 28, 2022 Series A; other investors reported include Qualcomm Ventures.
“Backed by multiple venture investors including Owl Ventures, Qualcomm Ventures, Sierra Ventures, and LG Ventures”
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Director of AI (Physical AI)
Location: Dallas
Travel: Up to 20%
Reports To: Chief Technology Officer
About DeepHow
DeepHow is redefining how industrial knowledge is captured, structured, and shared through the power of AI. Our platform uses advanced computer vision, natural language processing, and large language models to transform expert know-how into intelligent, searchable, and multilingual training workflows. DeepHow empowers manufacturers and service organizations to digitize tribal knowledge, accelerate onboarding, and drive operational excellence at scale. With 100+ enterprise customers and deep integrations across MES, LMS, and ERP systems, DeepHow combines AI innovation with real-world industrial expertise—bridging people, process, and performance across the modern enterprise.
Position Overview
This role is designed for a senior technical leader with deep hands-on engineering experience in Physical AI systems. You will lead the development, fine-tuning, and real-world deployment of Large Language Models (LLMs) and Vision-Language Models (VLMs) that interact with physical environments and industrial systems.
Key Responsibilities
• Lead the fine-tuning and optimization of Vision-Language Models (VLMs) and Large Language Models (LLMs) to improve spatial reasoning, object interaction, and environmental understanding.
• Remain hands-on in the engineering lifecycle, including architecture design, code development, and rigorous technical reviews.
• Serve as the primary technical authority, translating complex AI architectures and autonomous system behaviors into clear, actionable insights for non-technical customers and executives.
• Travel to customer and partner sites to oversee integration of AI software with physical hardware, ensuring reliability and performance in diverse industrial conditions.
Required Qualifications
• Master’s or PhD in Computer Science, Robotics, Electrical Engineering, or a related discipline.
• Extensive background as a software engineer with a proven history of building, shipping, and maintaining complex, production-grade systems.
• Demonstrated expertise in fine-tuning Vision-Language Models (VLMs) and Large Language Models (LLMs) for domain-specific applications.
• Exceptional communication skills with the ability to explain complex algorithmic concepts clearly to non-technical stakeholders.
• Operational readiness and willingness to travel for on-site testing, deployment, and partner collaboration.
• Professional experience in industrial or manufacturing environments is a strong plus, especially deploying AI in real-world production settings.
DeepHow is an equal opportunity employer. We value diverse perspectives and are committed to building an inclusive team.
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