8 hours ago

Computer Engineering AI Data Trainer

Alignerr

Hybrid
Contractor
$110,000
Hybrid

Job Overview

Job TitleComputer Engineering AI Data Trainer
Job TypeContractor
Offered Salary$110,000
LocationHybrid

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Job Description

About The Job

At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models.

As a Computer Engineering AI Data Trainer, you’ll challenge advanced language models on topics like computer architecture and hardware design, embedded systems and IoT, networking and distributed systems, hardware security, and systems software and operating systems—documenting every failure mode so we can harden model reasoning.

This is an hourly contract position with Alignerr, offering competitive compensation ($35–$60 /hour) and flexible remote work (10–40 hours/week).

What You’ll Do

  • Develop Complex Problems: Design advanced computer engineering challenges across domains like RISC-V/ARM architecture, FPGA development, memory management, and hardware-software co-design.
  • Author Ground-Truth Solutions: Create rigorous, step-by-step technical solutions, including assembly code, hardware description language (HDL) snippets, and architectural diagrams that serve as "golden responses" for AI training.
  • Technical Auditing: Evaluate AI-generated code (C/C++, Verilog, VHDL), logic gate designs, and operating system kernels for technical accuracy, efficiency, and adherence to industry standards.
  • Refine Reasoning: Identify logical fallacies in AI reasoning—such as race conditions, memory leaks, or improper timing constraints—and provide structured feedback to improve the model's "thinking" process.

Requirements

  • Advanced Degree: Masters (pursuing or completed) or PhD in Computer Engineering, Computer Science with a hardware focus, or a closely related field.
  • Domain Expertise: Strong foundational knowledge in core areas such as Computer Architecture, Embedded Systems, Digital Logic Design, or Operating Systems.
  • Analytical Writing: The ability to communicate highly technical hardware concepts and low-level software logic clearly and concisely in written form.
  • Attention to Detail: High level of precision when checking bit-level operations, clock-cycle timing, and technical documentation.
  • No AI experience required

Preferred

  • Prior experience with data annotation, data quality, or evaluation systems.
  • Proficiency in engineering software concepts (e.g., SolidWorks, MATLAB, ANSYS) to evaluate AI-generated code or workflows.

Why Join Us

  • Competitive pay and flexible remote work.
  • Collaborate with a team working on cutting-edge AI projects.
  • Exposure to advanced LLMs and how they’re trained.
  • Freelance perks: autonomy, flexibility, and global collaboration.
  • Potential for contract extension.

Application Process

The application process takes 15-20 minutes and involves submitting your resume, completing a short screening, and project matching/onboarding. Our team reviews applications daily; please complete your AI interview and application steps to be considered for this opportunity.

Key skills/competency

  • Computer Architecture
  • Embedded Systems
  • Digital Logic Design
  • Operating Systems
  • Hardware-Software Co-design
  • RISC-V/ARM Architecture
  • FPGA Development
  • Memory Management
  • Technical Writing
  • AI Model Training

Tags:

Computer Engineering
AI Data Trainer
Model Evaluation
Hardware Design
Embedded Systems
Operating Systems
RISC-V
ARM
FPGA
Verilog
VHDL
C/C++
Technical Writing
Data Annotation
LLMs
MATLAB
SolidWorks
ANSYS
Remote Work
Contract

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How to Get Hired at Alignerr

  • Research Alignerr's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume: Highlight advanced degrees, computer engineering expertise, and analytical writing skills to align with the Computer Engineering AI Data Trainer role at Alignerr.
  • Showcase domain mastery: Emphasize experience in computer architecture, embedded systems, and digital logic design relevant to AI data training.
  • Prepare for technical challenges: Be ready to discuss complex hardware concepts, low-level software logic, and your attention to detail in technical auditing.
  • Demonstrate problem-solving: Articulate how you would identify and refine logical fallacies in AI reasoning, providing structured feedback for model improvement.

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