Computer Engineering — AI Data Trainer

About The Role

We're partnering with the world's leading AI research labs to build smarter, more reliable AI systems — and we need expert computer engineers to help get there. As a Computer Engineering AI Data Trainer, you'll put your deep technical knowledge to work challenging, auditing, and refining advanced language models on the topics you know best.

This is a rare opportunity to work at the frontier of AI development, directly influencing how next-generation models reason about hardware, systems, and low-level software.

Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week

What You'll Do

Design Complex Technical Problems — Craft advanced computer engineering challenges spanning RISC-V/ARM architecture, FPGA development, memory management, and hardware-software co-design Author Ground-Truth Solutions — Produce rigorous, step-by-step reference solutions including assembly code, HDL snippets (Verilog/VHDL), and architectural diagrams that serve as benchmarks for AI training Audit AI-Generated Outputs — Evaluate AI-produced code (C/C++, Verilog, VHDL), logic gate designs, and OS kernels for technical accuracy, efficiency, and adherence to industry standards Identify and Fix Reasoning Failures — Spot logical flaws like race conditions, memory leaks, and improper timing constraints, then provide structured feedback to improve model reasoning Stress-Test AI Knowledge — Challenge models on computer architecture, embedded systems and IoT, networking, distributed systems, hardware security, and systems software

Who You Are

Pursuing or holding a Master's or PhD in Computer Engineering, Computer Science (hardware focus), or a closely related field Strong foundational expertise 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 in writing Highly precise — comfortable working with bit-level operations, clock-cycle timing, and technical documentation Self-motivated and able to work independently and asynchronously No prior AI experience required

Nice to Have

Experience with data annotation, data quality evaluation, or AI evaluation workflows Proficiency with engineering tools such as MATLAB, SolidWorks, or ANSYS Hands-on experience with FPGA toolchains, embedded platforms, or RTL design

Why Join Us

Work on cutting-edge AI projects with top research labs and AI teams Fully remote and flexible — work on your own schedule Freelance perks: autonomy, variety, and global collaboration Gain rare, insider exposure to how advanced LLMs are built and trained Potential for ongoing work and contract extension