Computer Engineering

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

Benefits offered by this job

Competitive pay

Flexible remote work

Job summary

Alignerr is seeking a Computer Engineering - AI Data Trainer for remote, hourly work. You will design advanced hardware/software challenges, author golden solutions including HDL snippets, and assess AI-generated code for correctness and efficiency.

Youll help improve model reasoning by identifying edge cases and documenting failure modes, enabling robust AI training. A Masters or PhD in a hardware-focused field is preferred, with strong knowledge in computer architecture and embedded systems.

Qualifications

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

Responsibilities

• Develop complex problems across domains like RISC-V/ARM architecture, FPGA development, memory management, and HW-SW co-design.
• Author ground-truth solutions with step-by-step technical content including HDL snippets and diagrams.
• Technical auditing of AI-generated code (C/C++, Verilog, VHDL), gate designs, and OS kernels for accuracy and efficiency.
• Refine AI reasoning by identifying logical fallacies and timing issues, providing structured feedback.

Education

Masters or PhD in Computer Engineering/CS with hardware focus

Job description

Computer Engineering - AI Data Trainer

Location: Remote

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.

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.