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.

Computer Engineering - AI Data Trainer

Location:

Remote

Type:
Hourly Contract

Compensation: $35–$60 /hour

Commitment: 10–40 hours/week

• 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.

• 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.

• Prior experience with data annotation, data quality, or evaluation systems.
• Proficiency in engineering software concepts (e.g., Solid Works, MATLAB, ANSYS) to evaluate AI-generated code or workflows.

• 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.