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Data Annotation Ai Training Jobs in Texas (NOW HIRING)

YO AI Labs

SWE AI Training Data Expert - Remote

Dallas, TX · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

YO AI Labs

SWE AI Training Data Expert - Remote

Austin, TX · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

YO AI Labs

SWE AI Training Data Expert - Remote

Houston, TX · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong understanding of algorithms and data structures . * Experience with bug fixing and debugging ...

Giga Energy

AI Training & Enablement Lead

Austin, TX · On-site +1

We build data centers fast and at scale by combining the capabilities of an equipment supplier ... What you'll do Giga is hiring a full-time AI Training & Enablement Lead to build the learning and ...

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Infographic showing various Data Annotation Ai Training job openings in Texas as of August 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution.

SWE AI Training Data Expert - Remote

YO AI Labs

Dallas, TX • Remote

$80 - $120/hr

Full-time

Posted 8 days ago

Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: Remote

Job Summary

We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.