Computer Engineering

Job summary

You will design complex computer engineering challenges and author rigorous, step-by-step technical solutions to train AI models. Additionally, you will perform technical audits on AI-generated code and logic designs to refine model reasoning and accuracy.

Job details

Computer Engineering - AI Data Trainer Location: Remote About the job At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models. You’ll challenge advanced language models on topics like computer architecture and hardware design, embedded systems and IoT, networking and distributed systems, hardware security, and systems software and operating systems—documenting every failure mode so we can harden model reasoning. Organization: Alignerr Position: Computer Engineering - AI Data Trainer Type: Hourly Contract Compensation: $35–$60 /hour Location: Remote Commitment: 10–40 hours/week What You’ll Do: - Develop Complex Problems: Design advanced computer engineering challenges across domains like RISC-V/ARM architecture, FPGA development, memory management, and hardware-software co-design. - Author Ground-Truth Solutions: Create rigorous, step-by-step technical solutions, including assembly code, hardware description language (HDL) snippets, and architectural diagrams that serve as "golden responses" for AI training. - Technical Auditing: Evaluate AI-generated code (C/C++, Verilog, VHDL), logic gate designs, and operating system kernels for technical accuracy, efficiency, and adherence to industry standards. - Refine Reasoning: Identify logical fallacies in AI reasoning—such as race conditions, memory leaks, or improper timing constraints—and provide structured feedback to improve the model's "thinking" process. Requirements: - Advanced Degree: Masters (pursuing or completed) or PhD in Computer Engineering, Computer Science with a hardware focus, or a closely related field. - Domain Expertise: Strong foundational knowledge in core areas such as Computer Architecture, Embedded Systems, Digital Logic Design, or Operating Systems. - Analytical Writing: The ability to communicate highly technical hardware concepts and low-level software logic clearly and concisely in written form. - Attention to Detail: High level of precision when checking bit-level operations, clock-cycle timing, and technical documentation. - No AI experience required Preferred Prior experience with data annotation, data quality, or evaluation systems - Proficiency in engineering software concepts (e.g., SolidWorks, MATLAB, ANSYS) to evaluate AI-generated code or workflows. Why Join Us: - Competitive pay and flexible remote work. - Collaborate with a team working on cutting-edge AI projects. - Exposure to advanced LLMs and how they’re trained. - Freelance perks: autonomy, flexibility, and global collaboration. - Potential for contract extension. Application Process (Takes 15-20 min) - Submit your resume - Complete a short screening - Project matching and onboarding PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

What you’ll do

You will design complex computer engineering challenges and author rigorous, step-by-step technical solutions to train AI models. Additionally, you will perform technical audits on AI-generated code and logic designs to refine model reasoning and accuracy.

Requirements

Candidates must hold or be pursuing a Masters or PhD in Computer Engineering, Computer Science, or a related field with a hardware focus. Strong foundational knowledge in computer architecture, embedded systems, and digital logic design is required, along with excellent analytical writing skills.

Benefits

• Competitive pay • Flexible remote work • Global collaboration

Listed skills

• Verilog · Preferred
• VHDL · Preferred
• Embedded Systems · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Computer architecture
• Embedded systems
• IoT
• Networking
• Distributed systems
• Hardware security
• Operating systems
• RISC-V
• ARM architecture
• FPGA development
• Memory management
• Hardware-software co-design
• C/C++
• Verilog
• VHDL
• Technical auditing

Job areas

• Technology
• Engineering
• Software
• Data & Analytics
• Science & Research