AI/Systems Engineer — NeoHuman

Company: Emergences Labs

About the Company: Emergences Labs (emergences.ai) is a small, research-driven, VC-backed team building NeoHuman — a desktop-first system that observes how people actually use AI tools, files, and workflows during real tasks, and turns those sessions into reliable evaluation evidence. They've published the AgentIF-OneDay benchmark and are now scaling the infrastructure underneath it. Visa sponsorship available.

Job Category: AI Engineering / Systems Engineering / Desktop Software / Research Infrastructure

Contract Type: Full-Time, Permanent

Location: Remote — USA (LA or SF preferred but nationwide)

Salary: $120,000–$150,000 + equity

Application Email: [email protected] (Subject: "Your Name — AI / Systems Engineer"; include resume and a note on a system you've built)

Posted: May 14, 2026 (posted directly by the company on HN Who's Hiring May 2026)

Job Description: You'll build the infrastructure that captures how people use AI in real tasks — desktop software that observes file access, app switching, typing patterns, and workflow decisions — and turn those sessions into training and evaluation data for AI systems. This is serious systems engineering work with direct research impact.

Key Responsibilities:

• Build and scale NeoHuman's desktop capture and evaluation infrastructure
• Design systems that capture real-task AI usage: what someone typed, what they copied, what they verified, how they moved across apps
• Build data pipelines for evaluation evidence generation from captured sessions
• Contribute to AI evaluation infrastructure supporting the AgentIF-OneDay benchmark
• Work closely with the research team to make capture data useful for training and evaluation

Skills Required: Desktop software engineering (macOS/Windows), Python, AI infrastructure, data pipelines, low-level debugging, systems programming.

Requirements:

• Strong systems engineering background — desktop software, AI infrastructure, data pipelines, or low-level debugging
• Interest in AI evaluation and research infrastructure
• Comfortable working in a small, research-driven team
• Clear, concise written communication for an async-heavy team