Ethos's AI interviewer asks about your career, then matches you to projects like Software Engineer. Keep your CV open and cover these:

4+ years as a software engineer, data engineer

4+ years as a software engineer, data engineer

Direct experience evaluating model outputs or system readiness and documenting technical tradeoffs

Direct experience evaluating model outputs or system readiness and documenting technical tradeoffs

We're working with a leading foundational AI lab to find experienced software engineers who can help train their latest language model on professional document, spreadsheet, and slide deck tasks.

We're looking for software engineers with 4+ years building software, AI/ML systems, or data infrastructure in a skilled engineering or data role to create, evaluate, and refine AI-generated documents, spreadsheets, and slide decks across core workflows: technical design documents and architecture decision records, data pipeline and ETL documentation, model evaluation and AI system readiness reports, API specification and integration guides, data quality and validation test plans, and developer onboarding guides and system architecture diagrams.

Flexible, 5-20 hours per week (or more if desired)

Fully remote, work on your own schedule

ASAP

4+ years as a software engineer, data engineer, or AI/ML practitioner writing technical design documents, data pipeline documentation, or API specifications

Direct experience evaluating model outputs or system readiness and documenting technical tradeoffs for engineering or cross-functional stakeholders

Ethos's AI interviewer asks about your Software Engineer background. These are our own practice questions for that work, not Ethos's.

I design around the parts of the problem I'm confident are stable,



like the core data model, and keep the parts most likely to change, like specific business rules, isolated behind clear interfaces. I add targeted logging around the suspected area and compare production data or configuration against my local setup, since an issue that's environment-specific usually traces back to a real difference between the two rather than a fundamentally different bug. How do you decide when a piece of code needs a test versus when it's low-risk enough to skip?

I prioritize tests for logic with real business consequences if it breaks, or code that's likely to be touched again later by someone unfamiliar with it. Simple, rarely-changed glue code gets less coverage, since the cost of a thorough test there often exceeds the risk it's protecting against.

How do you evaluate a proposed technical solution's trade-offs, like performance versus maintainability?

I start from the actual constraint that matters for this specific system, whether that's genuinely performance-critical or whether maintainability is the bigger long-term cost, rather than defaulting to whichever trade-off I personally prefer. Optimizing for performance the system doesn't need just adds complexity nobody benefits from.

See all 10 Software Engineer interview questions →

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When your profile is live, Ethos matches you to new projects from your career history, so companies find you. Each finished project raises your Expert Score, which brings you better-paid work.

Within 30 days of your invoice, after a project closes. Some AI training platforms pay weekly, so plan for the longer wait.

How many hours a week is this Software Engineer work?

What experience does this Software Engineer listing ask for?

The listing asks for 4+ years as a software engineer, data engineer, or AI/ML practitioner writing technical design documents, data pipeline documentation, or API specifications; direct experience evaluating model outputs or system readiness and documenting technical tradeoffs for engineering or cross-functional stakeholders; Coding is named directly in the listing. If you don't have hands-on experience with this, expect the screening to test for it.

This listing is posted at $80/hr, an hourly rate. Ethos's AI interviewer asks about your career in a 5 to 15 minute call, builds your profile from it, and then matches you to projects like this one. It raised a $22.75M Series A led by a16z in May 2026, with General Catalyst and XTX Markets participating, and works with AI labs, private equity firms, hedge funds and consultancies. it doesn't affect your pay or the projects you're offered.

📌 Expert Software Engineer - Remote (Canada)
🏢 Ethos
📍 Canada