Azure OpenAI Developer — Code Review & Evaluation

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect people with projects that shape how modern AI behaves and provide opportunities to grow skills in the human side of AI.

Why AI Training Work Matters

AI training (data labeling / annotation / human feedback) is how AI systems learn from real examples and human judgment. Contributors work on tasks like reviewing model responses, evaluating code outputs, and labeling datasets—work that directly improves production AI behavior.

• 100% remote and flexible — fit tasks around your schedule.
• Accessible: many projects require domain knowledge or attention to detail rather than formal credentials.
• Impactful: your feedback will improve how AI systems advise developers working in Azure.

The Role

We are looking for an experienced OpenAI (Azure) developer to evaluate AI-generated code, review prompts/responses about Azure OpenAI usage, and conduct technical interviews for candidates applying to Azure OpenAI roles. Your evaluations will be used to label, categorize, and improve model outputs so they reflect correct Azure practices.

• Work type: Contract, part-time (less than 20 hours/week).
• Remote: Worldwide.
• Labeling focus: computer programming / coding outputs related to Azure OpenAI.

What You'll Do

This is a mixed evaluation and interviewing role. Expect to analyze AI-generated answers, run structured technical assessments with human candidates, and produce clear, actionable feedback used to train models and improve outreach materials.

• Review and label AI-generated prompts and code responses for accuracy, relevance, and best practices in Azure OpenAI contexts.
• Assess authentication, model deployment, API integration, and performance optimization recommendations.
• Conduct AI-driven technical interviews to verify hands-on experience and English communication clarity.
• Provide structured, written feedback and corrections suitable for training datasets.

Interview & Labeling Tasks (Examples)

You will follow a structured interview plan and labeling rubric. Examples below mirror tasks you will perform — use them to demonstrate how you'd probe depth and judge candidate answers.

• Ask candidates to describe real-world projects deploying GPT/Codex/DALL·E via Azure OpenAI and probe for specifics (authentication, scaling, integrations).
• Present this buggy Python snippet and ask the candidate to find issues and explain fixes: import openai\n\nopenai.api_base = "https://your-azure-openai-endpoint.com/"\nopenai.api_key = "your-api-key"\n\nresponse = openai.ChatCompletion.create(\n model="gpt-4",\n messages=[{"role": "user", "content":
• Ask candidates to correct statements such as: "Azure OpenAI Service allows you to train and fine-tune models using built-in AutoML capabilities." and request the correct explanation.
• Evaluate candidates on ability to explain Azure AD / managed identity authentication, rate limits, token usage optimizations, and model deployment best practices.

Requirements

Do not apply unless you meet the concrete technical expectations below. Accuracy and real hands-on experience are mandatory; this role rejects purely theoretical answers.

• 5+ years hands-on experience working with Azure OpenAI Service, model deployment, API integration, and fine-tuning OpenAI models in Azure (explicit requirement).
• Deep familiarity with Azure authentication patterns (Azure AD, managed identities) and cloud deployment of AI workloads.
• Proven ability to debug and optimize OpenAI API implementations for performance and cost.
• Strong English writing and communication skills — you will produce clear, structured feedback and run interviews.
• Comfort labeling code and technical text according to a rubric and producing concise corrections.

Compensation, Schedule & Tools

This is a contract, part-time role paid per hour at the listed rate. You will use provided labeling tools (OTHER) and follow project-specific rubrics.

• Pay: USD 20.00 per hour.
• Time commitment: Less than 20 hours per week (flexible scheduling).
• Employment type: Contractor, Part-time.
• Label types: Computer programming / coding; labeling software will be provided (listed as OTHER).

How To Apply

If you meet the requirements and want to help train AI to give accurate Azure guidance, apply with a short summary of relevant projects and examples of past Azure OpenAI deployments or integrations. Include a brief sample of written technical feedback (1–3 short paragraphs) correcting or improving an AI-generated code response.

• Describe two production scenarios where you deployed OpenAI models on Azure and the specific challenges you solved.
• Attach one example of structured feedback you would give on a buggy API implementation (200–400 words).