Customer & Solutions · London / San Francisco / New York · Full-time · Mid level
This role asks for a software engineer who can take a data platform into demanding customer environments and build production software there. A strong candidate brings several years of full stack engineering, sound system design judgment, and comfort working directly with customer engineering teams on unclear problems. Ownership from scoping through rollout matters more than any single language.
How it fits the AI era
The work sits close to teams training physical AI systems, so the engineer deals with messy real world data and the pipelines around it. AI tools can speed up coding and debugging, but deciding what to build for a given customer and earning their trust stays human. The role also turns repeated customer problems into reusable product features, which is judgment work.
How it builds AI experience
Building here means learning how AI teams prepare video, sensor and image data for robots and autonomous systems, and how labeling and cleaning workflows hold up in production. That grounding in data pipelines for physical AI is hard to get elsewhere. A candidate can prepare by getting hands on with data tooling and ML workflows before applying.
Worth showing
- End to end ownership
- Customer facing technical work
- Python and data workflows
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
About Encord
A data platform that helps AI teams manage, label and clean the video, sensor and image data that trains robots, self-driving cars and other physical AI systems.
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