Computer Engineering Expert — AI Content Specialist
About The Role
We're partnering with the world's leading AI research labs to build smarter, more technically rigorous AI models — and we need experts like you to make it happen. 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.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week (flexible)
What You'll Do
- 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
Who You Are
- Holds or is pursuing a Master's or PhD in Computer Engineering, Computer Science (hardware focus), or a closely related field
- Deep foundational knowledge in one or more of: Computer Architecture, Embedded Systems, Digital Logic Design, or Operating Systems
- Able to communicate complex hardware concepts and low-level software logic clearly and precisely in writing
- High attention to detail — comfortable working at the level of bit operations, clock cycles, and timing constraints
- No prior AI or data annotation experience required
Nice to Have
- Prior experience with data annotation, data quality, or AI evaluation workflows
- Familiarity with engineering tools such as MATLAB, ANSYS, or hardware simulation environments
- Hands-on experience with embedded platforms, FPGAs, or real-time systems
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
