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Weekday is seeking insurance experts to build and judge tasks for an AI training and evaluation project. This is an internal, contract-based role with remote work and flexible hours, paying ₹20,000–₹25,000 per task.
You’ll design underwriting scenarios and review AI-generated decisions, providing precise, defendable rationales for each evaluation. Prior underwriting, claims, or risk assessment experience is essential; nitric detail and deadline reliability are valued.
This is an internal role at Weekday. Not a role by a client.
Weekday is an AI-native recruiting platform. We are backed by Y Combinator and Venture Highway (now General Catalyst). We have built the largest white-collar talent database in India and have built tools to run outbound recruiting campaigns to them.
We are now running an AI training and evaluation project as a YC-backed AI data lab, and we're looking for insurance experts to build and judge the tasks that advanced AI models get tested on.
₹20,000 - ₹25,000 a day
Advanced AI models are being pushed into insurance work — underwriting decisions, risk assessment, claims adjudication. Whether they're actually any good at it depends on the quality of the people who train and test them. That's you.
You'll create complex underwriting and claims tasks that a model should be able to handle but often can't, and you'll evaluate what the model produces — where it's right, where it's subtly wrong, and where it's confidently making things up. The work rewards precision. A vague scenario or a lazy evaluation is worse than none at all.
This is not back-office processing and it's not data entry. Each task is a piece of real insurance judgement — the kind of call a senior underwriter or claims assessor would have to get right and be able to defend. If you want templated, repetitive work, this isn't for you. If you like taking a messy risk or a contested claim apart and explaining exactly why a decision is wrong, you'll probably enjoy it.
On any given task you might be:
Every task is reviewed. You'll be measured on the quality and rigour of what you submit, not on volume.