STEM Researcher — Physics or Mathematics PhD

Posted 72d ago

Posted by Karokan

karokan.ai

€90–160/hr

Sciences RemoteHourly Contract

7 hired this month

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Role Overview

Design verifier-backed reasoning tasks for advanced STEM evaluation and post-training refinement of frontier models.

Karokan is working with AI labs and deployment teams across Europe to contract high-judgment specialists who can improve model quality through reliable human input. This role is designed for experts who can translate nuance into structured outputs, work with clear evaluation rules, and contribute directly to the performance of production AI systems.

You will operate in a fully remote setting, collaborate asynchronously, and help shape datasets, reviews, and decision layers that support the next generation of AI products. The work is intentionally rigorous: accuracy, consistency, and written reasoning matter more than generic throughput.

Key Responsibilities

Author verifiable math and physics problems at PhD difficulty
Evaluate model reasoning traces for correctness and logical validity
Design automated verifiers for deterministic STEM benchmarks

Ideal Qualifications

PhD in mathematics, physics, or related STEM field
Experience writing competition-level math or proof-based problems

Fluent in French or Italian

More About The Opportunity

Expected commitment: 8–15h / week
Work arrangement: Evaluation
Location coverage: Remote
Languages relevant to this scope: French, Italian
Weekly payout reference: €2.7k

Contract And Payment Terms

You will be engaged as an independent contractor.
This is a remote role that can be completed on a flexible schedule within project expectations.
Project duration, scope, and throughput can expand or contract depending on team needs and performance.
Payments are issued weekly against approved work delivered.
Final onboarding may require location and contractor eligibility checks before activation.

About Karokan

Karokan partners with AI labs and enterprises across Europe to place high-performance talent into evaluation, research, and deployment workflows. The focus is practical: faster hiring, stronger human judgment, and more reliable AI systems built with people who understand the work in depth.

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