Computer Engineering

Computer Engineering — AI Data TrainerAbout The RoleWe'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: AlignerrType: Hourly ContractLocation: RemoteCommitment: 10–40 hours/weekWhat You'll DoDesign Complex Technical Problems — Craft advanced computer engineering challenges spanning RISC-V/ARM architecture, FPGA development, memory management, and hardware-software co-designAuthor 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 trainingAudit 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 standardsIdentify and Fix Reasoning Failures — Spot logical flaws like race conditions, memory leaks, and improper timing constraints, then provide structured feedback to improve model reasoningStress-Test AI Knowledge — Challenge models on computer architecture, embedded systems and IoT, networking, distributed systems, hardware security, and systems softwareWho You ArePursuing or holding a Master's or PhD in Computer Engineering, Computer Science (hardware focus), or a closely related fieldStrong foundational expertise in one or more of: Computer Architecture, Embedded Systems, Digital Logic Design, or Operating SystemsAble to communicate complex hardware concepts and low-level software logic clearly in writingHighly precise — comfortable working with bit-level operations, clock-cycle timing, and technical documentationSelf-motivated and able to work independently and asynchronouslyNo prior AI experience requiredNice to HaveExperience with data annotation, data quality evaluation, or AI evaluation workflowsProficiency with engineering tools such as MATLAB, SolidWorks, or ANSYSHands-on experience with FPGA toolchains, embedded platforms, or RTL designWhy Join UsWork on cutting-edge AI projects with top research labs and AI teamsFully remote and flexible — work on your own scheduleFreelance perks: autonomy, variety, and global collaborationGain rare, insider exposure to how advanced LLMs are built and trainedPotential for ongoing work and contract extension