Technical Sourcer Intern
Technical Sourcer Intern
Paid internship, Fall 2026
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Company |
NGV Talent |
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Location |
Remote (United States) |
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Term |
Fall 2026, approximately September through December 12 |
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Hours |
15 to 20 per week, flexible around class schedule |
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Compensation |
$15.00-$20.00 per hour, W-2 |
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Academic credit |
Optional. NGV will complete a learning agreement, supervisor evaluations, and any university paperwork required for credit. |
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Reports to |
Lead Technical Recruiter |
About NGV Talent
NGV Talent is a technical recruiting and staffing agency partnering with companies across autonomous vehicles, robotics, AI, and advanced technology. Our engineering and technical practice fills specialized roles in perception, autonomy, embedded systems, machine learning, and simulation for companies building at the front edge of the industry.
Position Summary
The Technical Sourcer Intern supports NGV’s engineering and technical recruiting team through research. The intern investigates companies, markets, and technical talent across autonomous vehicles, robotics, and applied AI, working through large volumes of unstructured information to surface what actually matters to a given search.
The role is built around learning a research method and applying it in a live environment. The intern works under direct supervision and does not carry independent responsibility for client deliverables or candidate outreach.
What You Will Take Away
The skills built in this internship are research skills first. They transfer to consulting, competitive intelligence, corporate development, investment research, product marketing, and any role that requires making sense of an industry from the outside.
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Structured research method: framing an ambiguous question, deciding where to look, and recognizing when you have enough to act
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Signal from noise: working through large volumes of unstructured information and judging what is actually important versus what is merely available
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Source and claim evaluation: understanding what a public signal genuinely demonstrates and where it misleads
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Company and market evaluation: reading funding stage, headcount trajectory, site footprint, and competitive position across a large company set
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Technical domain fluency in autonomous systems, robotics, and applied AI, sufficient to read the engineering landscape and understand what roles require
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Communicating research concisely to people who have to make decisions from it
Ongoing Responsibilities
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Research technical roles and build working knowledge of technologies including C++, Python, ROS/ROS2, perception, computer vision, machine learning, embedded systems, simulation, and autonomy
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Use LinkedIn Recruiter and other sourcing platforms to identify engineering candidates against criteria set by the supervising recruiter
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Build targeted candidate lists by technical requirement, experience, location, and seniority, for recruiter review
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Enrich and verify candidate profiles using public technical sources including GitHub, conference proceedings, publications, and patents
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Maintain candidate and market research in the applicant tracking system
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Learn how AI tools and AI recruiting agents are applied to sourcing, research, and recruiting workflows
Learning Objectives
These are starting objectives. Final objectives will be developed jointly by the intern, the site supervisor, and the faculty sponsor at the start of the term, and mapped to the intern’s academic program.
By the end of the term, the intern will be able to:
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Read a technical job description in the AV or robotics domain and explain the underlying engineering functions, adjacent skill sets, and the difference between required and transferable experience
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Construct and iterate Boolean search strings that isolate narrow technical populations, and explain why a given string over-returns or under-returns
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Execute a structured research process against an open-ended question, including source selection, prioritization, and knowing when the research is sufficient
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Work through a high volume of unstructured information and separate what is decision-relevant from what is not
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Evaluate technical credibility signals from public sources and articulate what each does and does not demonstrate
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Explain how a specialized recruiting firm engages with high-growth technology clients, from intake through pipeline development
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Summarize research clearly and concisely for colleagues who will act on it
Qualifications
Required
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Currently enrolled in a bachelor’s or master’s degree program, or a recent graduate
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Strong research and analytical skills, with the ability to structure ambiguous questions
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Ability to learn technical concepts quickly and understand complex job requirements
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Attention to detail and organizational discipline
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Strong written and verbal communication
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Comfortable working independently in a remote environment
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Eligible to work in the United States and residing in a state where NGV Talent is able to run payroll
Preferred
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Coursework or personal interest in software engineering, machine learning, robotics, or AI
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Experience with Boolean search
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Familiarity with LinkedIn Recruiter, an ATS, or similar tools
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Experience using AI research tools
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Prior recruiting, sourcing, research, or business development exposure
Supervision and Structure
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Direct supervision by a named NGV professional with recruiting and industry experience
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Weekly one-on-one with the site supervisor
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Written midterm and final performance evaluations, provided to the intern and to the faculty sponsor where academic credit applies
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All platform access and research tools provided by NGV