Live opening · Posted 11 days ago
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About the role
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Company Description:
Curvia AI is a London, UK-based technology and AI solutions company that transforms complexity into opportunity through enterprise solutions, AI-powered automation, and data-driven insights. We build practical, scalable, and human-centred years of technology grounded in integrity, security, and responsible innovation.
About the Role:
We're looking for a high-taste engineer with a strong eye for quality — someone who's worked hands-on with preference data and rubric creation, and knows what separates a good example from a great one. You communicate clearly and can synthesize complex technical work the way a strong MAI dev would: concise, structured, and easy for others to act on. You're comfortable in ambiguous, fast-moving environments and default to shipping over deliberating.
Offer Details:
Pay: US $720 per day.
Commitments Required: At least 8 hours per day and a minimum of 40 hours per week, with an overlap of 4 hours with PST.
Mode of Work: Fully Remote
Number of positions: 200
Years of experience: 5+ years
Required Skills:
5+ yrs of proficiency in Python (especially building/maintaining pipelines and infra) or Typescript/Golang/JavaScript (experience contributing to or navigating large codebases like VSCode a plus)
Hands-on experience with preference data collection and/or rubric creation
Strong written and verbal communication — able to distill technical work into clear, actionable summaries
Demonstrated high-taste judgment — able to articulate why something is good, not just that it is
What does day-to-day look like:
Design, refine, and iterate on rubrics and evaluation criteria for preference data
Review and label data with a high bar for quality, catching subtle issues others might miss
Build and maintain pipelines/infra that support data generation, collection, and evaluation workflows
Synthesize findings from data work into clear write-ups, updates, or recommendations for the team
Collaborate closely with researchers/engineers to translate qualitative judgment into scalable processes
Work arrangement
Yes
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