About the role
We're looking for great engineers with experience building the backend of highly performant systems that can handle very large volumes of unstructured and structured data. Customers use our platform to store, query, analyse, and manipulate billions of items of data — and we need to ensure these operations are fast and reliable at massive scale.
For this role we are particularly interested in engineers with experience in both traditional relational database systems like PostgreSQL and column-oriented analytics systems such as ClickHouse, who have worked on large-scale systems in industries where reliability and performance are critical.
You'll join a small, highly collaborative group at a crucial stage of accelerated development, operating with a high degree of autonomy and crafting performant, reliable, and maintainable solutions to challenging technical problems.
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.
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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.