Python – Senior Developers – AI Training – UK
About Prolific: Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers, researchers, and organisations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
Role
We’re looking for Senior Python Developers to join our Expert Network to help train and evaluate cutting‑edge AI models. If you have a background in Software Engineering, we will send you a quick 10‑ to 15‑minute test to assess your skills. If successful, you will be invited to join Prolific as a participant, where you will get paid to help AI understand and summarise complex scientific data. Researchers looking for your skills tend to pay up to $50/hr, depending on skills and experience level. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.
What you’ll bring
- Educational Background: a BSc or higher in Computer Science, Software Engineering, or a closely related technical field
- Professional Experience: real‑world experience as a Senior Software Engineer/Developer specialising in Python
- Coding Proficiency: ability to solve LeetCode Medium to Hard‑level problems in Python independently
- Deep Domain Knowledge: expert understanding of the GIL (Global Interpreter Lock), decorators, generators, memory management, and asynchronous patterns (asyncio, async/await)
- Code Quality: a high standard for clean code, including modularity, readability, and adherence to modern Pythonic standards (PEP 8, PEP 20)
- Attention to Detail: ability to spot subtle logical flaws, memory leaks, or security vulnerabilities in model‑generated code
What you’ll be doing in the role
- Evaluate Code Accuracy: review AI‑generated Python code for functional correctness and adherence to best practices
- Validate Logic & Reasoning: audit the step‑by‑step explanations provided by AI for complex algorithmic solutions to ensure they are logically sound
- Conduct Execution Testing: execute model‑generated scripts in appropriate environments to verify performance and output
- Annotate Model Performance: identify areas where a model provides inefficient solutions, deprecated syntax, or hallucinated library methods
- Refine Technical Logic: provide structured feedback on how models reason through backend architecture, data pipelines, or API design discussions
Key Technologies
- Core Language: expert mastery of Python 3.x, including type hints and modern language features
- Frameworks: extensive experience with Django, FastAPI, or Flask
- Testing & Tools: proficiency with pytest, unittest, coverage.py, and tox
- Backend & API: strong understanding of RESTful APIs, GraphQL, and server‑side logic in a Python environment (e.g., with FastAPI or Django REST Framework)
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