Remote AI Data Trainer: Computer Engineering

Alignerr; Ireland; On-site; EUR 42,000 - 71,000; Part time

Benefits offered by this job

Autonomy

Flexibility

Global collaboration

Job summary

Alignerr is seeking a Computer Engineering - AI Data Trainer to craft complex hardware challenges and reference solutions for AI training. This remote, hourly-contract role emphasizes rigorous evaluation of C/C++, Verilog/VHDL, and OS kernels, with a focus on ensuring accurate, high‑quality data for model training.

You will author step-by-step ground-truth solutions, audit AI outputs, and help refine model reasoning across architectures and co-design topics.

Qualifications

• Masters (pursuing or completed) or PhD in Computer Engineering, CS with hardware focus, or related field.
• Strong knowledge in Computer Architecture, Embedded Systems, Digital Logic Design, or Operating Systems.
• Ability to communicate highly technical hardware concepts clearly in writing.
• High precision in bit-level operations, clock-cycle timing, and technical documentation.
• No AI experience required.

Responsibilities

• Develop Complex Problems: Design advanced computer engineering challenges (RISC-V/ARM, FPGA, memory management).
• Author Ground-Truth Solutions with assembly code, HDL snippets, and diagrams for AI training.
• Technical Auditing: Evaluate AI-generated code (C/C++, Verilog, VHDL) and OS kernels for accuracy and standards.
• Refine Reasoning: Identify logical fallacies and provide feedback to improve model reasoning.

Skills

Hardware design

Embedded systems

Digital logic

Operating systems

Analytical writing

Attention to detail

No AI experience required

Education

Masters/PhD in Computer Engineering or CS with hardware focus

Tools

SolidWorks

MATLAB

ANSYS

Job description

Alignerr is seeking a Computer Engineering - AI Data Trainer to craft complex hardware challenges and reference solutions for AI training. This remote, hourly-contract role emphasizes rigorous evaluation of C/C++, Verilog/VHDL, and OS kernels, with a focus on ensuring accurate, high‑quality data for model training.

You will author step-by-step ground-truth solutions, audit AI outputs, and help refine model reasoning across architectures and co-design topics.