Computer Engineering

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

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.

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.

Computer Engineering - AI Data Trainer

• Location: Remote

Organization

Alignerr

Position

Computer Engineering - AI Data Trainer

Type

Hourly Contract

Compensation

$35–$60 /hour

Location

Remote

Commitment

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.