Remote AI Data Trainer: Computer Architecture & Hardware

Alignerr Corp.; Wellington; Remote; NZD 86,000 - 147,000; Full time

Benefits offered by this job

Flexible remote work

Global collaboration

Autonomy

Job summary

Alignerr is seeking a Computer Engineering - AI Data Trainer to join our remote team. You will design advanced hardware and AI data challenges and author rigorous solutions for training language models, covering RISC-V/ARM, FPGA, memory management, and HW-SW co-design.

Role emphasizes precise technical reasoning, validation of AI-generated code and OS kernels, and identifying issues such as race conditions and memory leaks. Masters/PhD preferred; remote contract 10–40 hours per week.

Qualifications

• Advanced degree in Computer Engineering, CS with hardware focus, or closely related field.
• Ability to communicate highly technical hardware concepts and low-level software logic clearly.
• High precision when checking bit-level operations, timing, and technical documentation.

Responsibilities

• Design advanced computer engineering challenges across RISC-V/ARM architecture, FPGA development, memory management, and HW-SW co-design.
• Create step-by-step technical solutions, including assembly, HDL snippets, and diagrams for AI training.
• Evaluate AI-generated code (C/C++, Verilog, VHDL) and OS kernels for accuracy and standards compliance.
• Identify and provide feedback on logical issues in AI reasoning such as race conditions and memory leaks.

Skills

Analytical writing

Attention to detail

Hardware concepts

Education

Masters/PhD in Computer Engineering/CS hardware focus

Tools

SolidWorks

MATLAB

ANSYS

Job description

Alignerr is seeking a Computer Engineering - AI Data Trainer to join our remote team. You will design advanced hardware and AI data challenges and author rigorous solutions for training language models, covering RISC-V/ARM, FPGA, memory management, and HW-SW co-design.

Role emphasizes precise technical reasoning, validation of AI-generated code and OS kernels, and identifying issues such as race conditions and memory leaks. Masters/PhD preferred; remote contract 10–40 hours per week.