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 Computer Engineering - AI Data Trainer Location: Remote Type: Hourly Contract Compensation: $35–$60 /hour 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 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. Benefits 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. #J-18808-Ljbffr