Computer Engineering

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

• 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

• 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

• Experience with data annotation, data quality evaluation, or AI evaluation workflows
• Proficiency with engineering tools such as MATLAB, Solid Works, or ANSYS
• Hands-on experience with FPGA tool chains, embedded platforms, or RTL design

• 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