Remote AI Hardware Engineer & Content Specialist

Alignerr Corp.; Sheffield (TX); Remote; USD 48,000 - 83,000; Full time

Benefits offered by this job

Autonomy

Flexibility

Global collaboration

Job summary

Alignerr is seeking a Computer Engineering Expert - AI Content Specialist to craft advanced computer engineering challenges across RISC-V/ARM, FPGA, memory management, and HW-SW co-design. You will document step-by-step, including assembly code and HDL snippets, to serve as golden responses for AI training.

You will also audit AI-generated code (C/C++, Verilog, VHDL) and OS kernels for correctness and efficiency, providing structured feedback to improve model reasoning.

Qualifications

• Advanced Degree: Masters (pursuing or completed) or PhD in Computer Engineering, Computer Science with a hardware focus, or a closely related field.
• Domain Expertise: Knowledge in Computer Architecture, Embedded Systems, Digital Logic Design, or Operating Systems.
• Analytical writing: ability to convey highly technical hardware concepts clearly in writing.
• Attention to Detail: precision in bit-level operations, clock-cycle timing, and technical documentation.
• No AI experience required.

Responsibilities

• Develop Complex Problems: Design advanced hardware challenges across domains like RISC-V/ARM, FPGA development, memory management, and HW-SW co-design.
• Author Ground-Truth Solutions: Create rigorous, step-by-step solutions with assembly code, HDL snippets, and architectural diagrams for AI training.

Skills

Analytical writing

Attention to detail

Education

Master's degree (pursuing or completed) in Computer Engineering or CS with hardware focus

Tools

SolidWorks

MATLAB

ANSYS

Job description

Alignerr is seeking a Computer Engineering Expert - AI Content Specialist to craft advanced computer engineering challenges across RISC-V/ARM, FPGA, memory management, and HW-SW co-design. You will document step-by-step, including assembly code and HDL snippets, to serve as golden responses for AI training.

You will also audit AI-generated code (C/C++, Verilog, VHDL) and OS kernels for correctness and efficiency, providing structured feedback to improve model reasoning.