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
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