OpenAI (Azure) Developer Needed for AI Code Review & Evaluation

About OpenTrain

OpenTrain is a centralized job board for data-labeling and AI-training roles. We gather projects from many AI companies and labeling platforms so you can find this kind of work in one place, create a free account, and apply in minutes.

About AI Training Work

AI training (data labeling / human feedback) is the human side of building intelligent systems. People annotate, review, and grade model outputs — including code and deployment advice — so AI tools become accurate, safe, and useful.

This project focuses on evaluating AI-generated technical content about Azure OpenAI Service. The work is remote and flexible, and your feedback will directly improve how models guide developers working with Azure OpenAI.

The Role

We are hiring a contractor to review and evaluate AI-generated OpenAI (Azure) code, configuration guidance, and deployment advice. You will conduct AI-driven interviews of candidates, analyze model responses, and produce structured labels and feedback that improve AI outputs.

This is a part-time contract role with flexible hours (under 20 hours per week). Pay is $20 USD per hour. Work is worldwide and remote.

• Pay: $20 USD per hour
• Time commitment: Less than 20 hours/week
• Employment types: Contractor, Part-time
• Location: Remote — worldwide

What You'll Do

Evaluate AI-generated prompts and responses about Azure OpenAI Service for accuracy, relevance, and adherence to best practices. Label, categorize, and rate outputs against expected technical guidance.

Conduct AI-driven technical interviews with candidates to verify hands-on experience and communication clarity. Provide structured, concise feedback on code snippets, authentication approaches, deployment configurations, and optimization suggestions.

• Analyze AI outputs for correct Azure OpenAI API usage and authentication methods.
• Assess model deployment configurations and cloud performance optimizations.
• Label code responses using provided schema, and write clear corrective comments and guidance.
• Run interview prompts to probe candidates' real-world Azure OpenAI experience and debugging skills.

Requirements

Candidates must have 5+ years of hands-on experience with Azure OpenAI Service, model deployment, API integration, and fine-tuning OpenAI models within the Azure ecosystem. You should be familiar with Azure-based authentication, managing AI workloads on cloud infrastructure, and optimizing API calls for enterprise use.

Strong English writing skills are essential because the role requires producing precise, structured feedback and conducting interviews that assess both technical depth and communication clarity.

• Minimum: 5+ years working with Azure OpenAI Service and related deployments
• Experience with Azure authentication (Azure AD, Managed Identities) for API calls
• Practical knowledge of scaling models, rate limits, and token-usage optimizations on Azure
• Able to produce clear, structured written feedback in English

Interview Process & Sample Tasks

You will follow an AI-driven interview script that probes five areas: real-world Azure OpenAI experience, debugging and optimization, AI evaluation and labeling skills, communication clarity, and task readiness/availability. The interview emphasizes hands-on examples and concrete problem-solving.

Interviewers will present AI-generated responses and code snippets, ask the candidate to find errors, correct them, and explain reasoning. Below is the example code snippet interviewers may use; candidates must identify issues and explain how to authenticate with Azure AD and scale deployments.

• Example snippet to debug and discuss: import openai openai.api_base = "https://your-azure-openai-endpoint.com/" openai.api_key = "your-api-key" response = openai.ChatCompletion.create( model="gpt-4", messages=[{"role": "user", "content": "Hello, world!"}] ) print(response)
• Sample evaluation prompts include correcting inaccurate claims such as: "Azure OpenAI Service allows you to train and fine-tune models using built-in AutoML capabilities."
• You must probe for specific projects, challenges, and fixes; reject candidates who provide only theoretical answers.

Who Should Apply

Apply if you have demonstrable, hands-on experience deploying and operating OpenAI models in Azure and can clearly explain authentication, deployment, and optimization strategies. This role suits technical reviewers who enjoy teaching, debugging, and improving AI-generated developer guidance.

Do not apply if your experience is only theoretical or you cannot provide concrete examples of real Azure OpenAI projects and debugging outcomes.

How It Works / How To Apply

Create a free OpenTrain account, review the project details, and submit your application. Be prepared to demonstrate past Azure OpenAI projects and to participate in a structured AI-driven interview that includes code review and labeling tasks.

Successful applicants will be contracted for part-time labeling and evaluation work, submitting labeled examples and written feedback through the project's labeling interface (labeled as OTHER). Payment is hourly at the rate above.

• Data type: Computer code (programming)
• Label types: COMPUTER_PROGRAMMING_CODING
• Labeling software: OTHER