DINQ has launched a new AI-native career network specifically designed to address what the company identifies as one of the most urgent and overlooked challenges in artificial intelligence: finding qualified and impact-driven talent. As AI adoption accelerates across industries, the primary constraint has shifted from capital or infrastructure to access to proven, skilled professionals. Despite increasing global demand for AI experts, most hiring platforms rely on outdated systems that fail to reflect how technical talent builds, collaborates, and grows.
Traditional resumes remain static documents, while keyword-based searches only function effectively when job descriptions are perfectly written. Many top AI researchers and engineers do not maintain LinkedIn profiles, and even when candidates are visible, their actual work—including code, research papers, and open-source contributions—often remains scattered and difficult to assess comprehensively. DINQ addresses this significant gap by creating a dynamic professional identity purpose-built for the AI era.
The core of the platform is the DINQ Card, which consolidates a user's research, repositories, and professional signals from platforms such as GitHub, arXiv, Google Scholar, and LinkedIn into one continuously updated profile. This enables hiring teams to evaluate candidates based on what they have built and contributed, rather than solely on where they have worked or their educational pedigree. "AI is not just changing how we hire. It is redefining what talent even means," said Sam Ko, founder and chief executive officer of DINQ. "In the AI era, resumes, titles, and static profiles are obsolete. What truly matters is the real signal: what you build, who you collaborate with, and how fast you evolve. AI talent recruitment must shift from keyword matching to understanding people as living systems."
Kelvin Sun, co-founder and chief operating officer of DINQ, emphasized that hiring for AI is increasingly about performance rather than pedigree. "Recruiters need to see how a candidate contributes, who they have worked with, and where their impact is visible. Our goal is to remove the guesswork and bring clarity to the hiring process," Sun stated. He brings experience from the talent and recruitment space, having previously served as the technology portfolio talent partner at Sequoia Capital China, where he advised on hiring and organizational growth for nearly 100 of the region's top technology startups.
The platform's launch timing aligns with the beginning of the 2026 hiring cycle, a period that historically sees increased hiring activity from companies initiating new projects and recent graduates entering the job market. DINQ aims to match this demand with improved discovery and faster, more accurate connections between talent and organizations. This addresses a critical industry need, as estimates suggest more than two million AI-related roles will remain unfilled globally in 2026. Recruiters report growing difficulty in sourcing qualified candidates despite record-level investment in AI and technical infrastructure.
The DINQ platform is now available at https://dinq.me, where users can create a DINQ Card at no cost and begin showcasing their work within minutes. By shifting the focus from traditional credentials to demonstrable impact and collaboration, DINQ's approach could fundamentally change how AI talent is discovered and evaluated, potentially increasing efficiency in a sector where talent scarcity represents a major bottleneck to innovation and implementation.
