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GTM Special Projects, Physical AI

Encord - New York | OnSite

Posted Jun 12, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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Mental health support
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Market context

U.S. role benchmark (BLS OEWS)
$57,704 U.S. median for this role
Projected growth (BLS Employment Projections)
+0.9% - Slower

Matched to SOC 41-2031 - Sales aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

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About this role

GTM Special Projects, Physical AI New York | OnSite About us Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator. The role Physical AI is our fastest-growing segment. Over the past 12 months, we've grown Physical AI revenue 10x. The companies building the next generation of robotics, autonomous vehicles, and intelligent physical systems have a data problem - and Encord is the only full-stack solution built to solve it. We're now building the founding sales team that will take this to market. This is a full-cycle commercial closing role on the ground floor of one of the most consequential verticals in AI. You'll own pipeline generation through close, selling into the world's most advanced Physical AI teams - robotics companies, autonomous vehicle programs, and research-driven enterprises like Boston Dynamics and Dyna. By day 30, you will have identified target accounts and booked meetings; by day 90, you will have closed your first pilot with a robotics or AV firm. You'll report to the Head of Physical AI and work in close partnership with our founders and GTM leadership. Pipeline generation support is in

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