At Alignerr, we partner with the world's leading AI research labs — and your deep technical knowledge is exactly what's needed to make these models smarter, more accurate, and more reliable.

You'll work directly on challenging problems in computer architecture, embedded systems, hardware design, and low-level software — stress-testing AI reasoning and shaping how these models think about complex engineering concepts. Your expertise becomes the benchmark.

Why Join Us

• Work on genuinely cutting-edge AI projects alongside top research labs.
• Fully remote and flexible — work the hours that suit you, from anywhere.
• Freelance autonomy with real intellectual challenge and impact.
• Gain rare, hands-on exposure to how advanced LLMs are built and trained.
• Potential for ongoing work and contract extension as projects grow.

• Design Advanced Engineering Challenges — Create rigorous, domain-specific problems spanning RISC-V/ARM architecture, FPGA development, memory management, hardware-software co-design, and more.
• Author Ground-Truth Solutions — Develop precise, step-by-step technical solutions including assembly code, HDL snippets, and architectural diagrams that serve as gold-standard references for AI training.
• Audit AI-Generated Technical Content — Evaluate AI outputs in C/C++, Verilog, and VHDL for correctness, efficiency, and adherence to industry standards.
• Refine AI Reasoning — Identify flaws in model logic — race conditions, memory leaks, improper timing constraints — and provide structured feedback that directly improves model performance.
• Challenge Model Limits — Push AI systems on topics like operating systems, networking, distributed systems, hardware security, and embedded IoT — documenting failure modes to harden reasoning.

• Pursuing or holding a Master's or PhD in Computer Engineering, Computer Science (hardware focus), or a closely related field.
• No prior AI experience required — if you know the engineering, we'll handle the rest.

Work arrangement: Fully remote

Eligible regions: Montreal