Data Engineer

AI Trainer Jobs; United States; Remote; USD 69,000 - 165,000; Full time

Job summary

AI Trainer Jobs is seeking qualified reviewers for a remote Data Engineer role. You will evaluate production code, reproduce failures, and write unit tests to guide model improvements.

This position emphasizes strong code-reading skills and precise reasoning to judge edge cases and correctness in AI-enabled data tasks. Responsibilities include running code in sandboxed environments, grading data engineering solutions for quality, and documenting findings with clear rationale.

Qualifications

• Strong ability to read, run, and debug unfamiliar code for Data Engineer tasks.
• Ability to write concise unit tests capturing a single failure mode.
• Familiarity with a testing framework: pytest, Jest, JUnit, Go test, RSpec, or equivalent.

Responsibilities

• Run and reproduce candidate code outputs in a sandboxed environment for Data Engineer assignments.
• Grade data engineering solutions for correctness, style, and edge-case handling.
• Write minimal failing tests that demonstrate bugs a model output missed.
• Compare paired solutions and rank them with a written rationale tied to the rubric.
• Tag failure modes (compile error, runtime crash, off-by-one, security issue) with severity scores.

Skills

Code review

Debugging

Unit testing

Software engineering judgment

Data engineering

AI

JAVA

JavaScript

MySQL

PostgreSQL

Python

Tools

pytest

Jest

JUnit

Go test

RSpec

Job description

Data Engineer is a remote engineering review track for evaluating production code, debugging traces, and developer-facing AI outputs against real-world correctness standards. Reviewers reproduce failures, write the unit test the model should have written, and explain the fix so the modeling team can target the gap.

Category: Coding, SWE & Agent Evaluation · Pay: $50–$120 / hr · Location: Remote — US-eligible · Contractor

Data Engineer is a remote engineering review track for evaluating production code, debugging traces, and developer-facing AI outputs against real-world correctness standards.

Role details

About the role

Data Engineer is a remote engineering review track for evaluating production code, debugging traces, and developer-facing AI outputs against real-world correctness standards. Reviewers reproduce failures, write the unit test the model should have written, and explain the fix so the modeling team can target the gap.
Engineering model quality lives or dies on whether the generated code actually compiles, passes tests, and handles edge cases. AuraOne pairs experienced engineers with the modeling team to grade outputs the way a code reviewer would.
Judge generated code and software engineering agents. Read their debugging traces.

Responsibilities

• Run and reproduce candidate code outputs in a sandboxed environment for Data Engineer assignments.
• Grade data engineering solutions for correctness, style, and edge-case handling.
• Write minimal failing tests that demonstrate the bug a model output missed.
• Compare paired solutions and rank them with a written rationale tied to the rubric.
• Tag failure modes (compile error, runtime crash, off-by-one, security issue) with severity scores.

What you should bring

• Strong day-job engineering experience — you can read, run, and debug unfamiliar code for Data Engineer work.
• Comfort writing concise unit tests that capture a single failure mode.
• Familiarity with a testing framework. pytest, Jest, or JUnit. Go test, RSpec, or whatever you use.
• Clear written reasoning — your review note has to convince another senior engineer.
• Reliable async availability for at least 10 hours per week.
• Prior code-review or technical-interview-grading experience is a plus.

Role signals

Example tasks

• Reproduce a generated engineering solution to a coding task, run the test suite, and grade it.
• Write the smallest failing test that demonstrates a model's edge-case bug.
• Compare two paired solutions and rank them with a written rationale tied to the rubric.
• Triage a security issue surfaced by a model and document the patch the model should have produced.

Useful experience

• Open-source contributions or a public portfolio that demonstrates production-quality code.
• Experience with the target language's standard tooling, linters, and idiomatic style guides.
• Familiarity with security-review checklists (OWASP, CWE) and AppSec patterns.

Compensation and schedule

$50–$120 / hr
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Code review
• Debugging
• Unit testing
• Software engineering judgment
• Data engineering
• AI
• JAVA
• JavaScript
• MySQL
• PostgreSQL
• Python

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.

• 01 Confirm profile and eligibility details.
• 02 Attach this role deliberately.
• 03 Receive a human review decision or follow-up.

Placement timing depends on program demand and reviewer confirmation.