About the role
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
We're opening our brand-new NYC office and looking for a founding Sales Director to lead US revenue growth. This is a rare opportunity to join as one of the first quota-carriers at a hyper-growth AI infrastructure startup — reporting directly to the Head of Global Sales and working alongside the co-founders. When successful, you'll build and lead the US commercial team.
Aplyr's read
Encord is a cutting-edge data management platform for computer vision, attracting tech-savvy professionals eager to innovate in AI and machine learning.
What's promising
- •Encord offers a specialized platform for efficient data labeling in computer vision projects.
- •The company is actively expanding, with numerous recent hires across engineering and growth roles.
- •Encord's focus on AI and machine learning positions it well in a rapidly growing industry.
What to watch
- •The niche focus on computer vision might limit opportunities for broader tech roles.
- •Rapid expansion could lead to growing pains in organizational structure and culture.
- •Limited public information about Encord's financial stability and long-term viability.
Why Encord
- •Encord specializes in human-in-the-loop systems for data workflows, enhancing machine learning accuracy.
- •The platform's emphasis on physical AI distinguishes it from general AI companies.
- •Encord's NYC and SF roles suggest a strategic focus on major tech hubs.
Aplyr’s read is generated by AI from public sources. Was it useful?
About Encord
Encord is a data management platform designed for computer vision projects, enabling teams to efficiently label, manage, and analyze training data for machine learning applications.
