Computer Engineering

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.

Position Summary

Computer Engineering – AI Data Trainer • Remote • Hourly Contract • $35–$60/hr • 10–40 hours/week

What You’ll Do

• Develop complex problems: Design advanced computer engineering challenges across domains such as 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, 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 (Master’s or PhD, pursuing or completed) in Computer Engineering, Computer Science with a hardware focus, or a closely related field.
• Strong foundational knowledge in core areas such as computer architecture, embedded systems, digital logic design, or operating systems.
• Analytical writing skills: ability to communicate highly technical hardware concepts and low‑level software logic clearly and concisely in written form.
• Attention to detail: high precision when checking bit‑level operations, clock‑cycle timing, and technical documentation.
• No prior 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.

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