As a Computer Engineering AI Content Specialist, you'll bring your deep knowledge of hardware design, computer architecture, and embedded systems to challenge and improve cutting-edge large language models (LLMs).

This is a rare opportunity to directly influence how AI reasons through complex engineering problems — from RISC-V pipelines to FPGA logic synthesis to operating system internals.

Why Join Us

• Work on genuinely cutting-edge AI projects alongside top research labs.
• Fully remote and flexible — work on your own schedule, on your own terms.
• Gain rare, insider exposure to how advanced LLMs are trained and evaluated.
• Contribute meaningful technical depth to AI systems used by millions.
• Freelance autonomy with the potential for ongoing, extended engagements.
• Be part of a global community of subject-matter experts pushing AI forward.

• Design Advanced Engineering Problems — Craft challenging, domain-specific problems spanning RISC-V/ARM architecture, FPGA development, memory management, hardware-software co-design, and more.
• Author Ground-Truth Solutions — Write rigorous, step-by-step technical solutions including assembly code, HDL snippets, and architectural diagrams that serve as gold-standard references for AI training.
• Audit AI-Generated Technical Content — Evaluate AI-produced C/C++, Verilog, and VHDL code along with logic gate designs and OS kernel implementations for correctness, efficiency, and standards compliance.
• Sharpen AI Reasoning — Identify flawed reasoning such as race conditions, memory leaks, and improper timing constraints, then provide structured feedback to improve how models think through hardware and systems problems.

• Holds or is pursuing 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: Mumbai