Your deep technical knowledge will directly shape how AI understands and reasons through complex hardware design, computer architecture, and embedded systems challenges.

This is a rare opportunity to apply your engineering expertise beyond traditional roles — working with world-class AI research teams to make AI smarter, more accurate, and more technically rigorous.

Why Join Us

• Work on cutting-edge AI projects alongside leading AI research labs.
• Fully remote and flexible — work on your own schedule.
• Freelance perks: autonomy, variety, and global collaboration.
• Contribute to meaningful work that shapes how AI reasons about technical problems.
• Potential for ongoing work and contract extension.

• Design Advanced Technical Challenges — Craft complex, domain-spanning problems across areas like RISC-V/ARM architecture, FPGA development, memory management, and hardware-software co-design that push AI models to their limits.
• Author Ground-Truth Solutions — Develop rigorous, step-by-step reference solutions including assembly code, HDL snippets (Verilog/VHDL), and architectural diagrams that serve as gold-standard training data.
• Audit AI-Generated Content — Critically evaluate AI outputs across C/C++, Verilog, VHDL, logic gate designs, and OS kernels for technical accuracy, efficiency, and alignment with industry standards.
• Improve AI Reasoning — Identify and document AI reasoning failures — such as race conditions, memory leaks, and improper timing constraints — and provide structured feedback to improve model behavior.

• Pursuing or holding a Master's or PhD in Computer Engineering, Computer Science (hardware focus), or a closely related field.
• No prior AI or data annotation experience required.

Work arrangement: Fully remote

Eligible regions: Atlanta