AI Data Trainer: Computer Engineering, Remote

Alignerr Corp.; Sheffield (TX); On-site; USD 50,000 - 83,000; Part time

Benefits offered by this job

Autonomy

Flexibility

Global collaboration

Job summary

Alignerr is seeking a Computer Engineering - AI Data Trainer for a remote hourly contract. You will challenge AI models on hardware topics and document failures to harden model reasoning. The role offers flexible hours and exposure to cutting-edge AI projects.

The ideal candidate has a Masters or PhD in a hardware-focused field with strong knowledge of architecture, embedded systems, and digital logic. No AI experience required, but data annotation experience is a plus.

Qualifications

• Masters or PhD in Computer Engineering, CS with hardware focus.
• Strong knowledge of computer architecture and digital logic.
• Experience explaining hardware concepts clearly in writing.
• Familiarity with HDL (Verilog/VHDL) is a plus.

Responsibilities

• Design advanced computer engineering challenges across domains such as RISC-V/ARM architecture, FPGA development, memory management, and hardware-software co-design.
• Create ground-truth solutions with step-by-step technical content including HDL snippets and diagrams.
• Audit AI-generated code (C/C++, Verilog, VHDL), logic gate designs, and OS kernels for technical accuracy and standards.
• Identify race conditions, memory leaks, and timing issues; provide feedback to improve model thinking.

Skills

Computer Architecture

Embedded Systems

Digital Logic Design

Operating Systems

Education

Masters or PhD

Tools

SolidWorks

MATLAB

ANSYS

Job description

Alignerr is seeking a Computer Engineering - AI Data Trainer for a remote hourly contract. You will challenge AI models on hardware topics and document failures to harden model reasoning. The role offers flexible hours and exposure to cutting-edge AI projects.

The ideal candidate has a Masters or PhD in a hardware-focused field with strong knowledge of architecture, embedded systems, and digital logic. No AI experience required, but data annotation experience is a plus.