Software Engineer Expert

Ethos; United States; Remote; USD 91,000 - 129,000; Part time

Job summary

Ethos is seeking a Software Engineer for fully remote, flexible 5–20 hours per week. Start date ASAP. Compensation is $80/hr with a plan to match project timelines. You set your own hours and work remotely, on your own schedule.

The role focuses on documenting technical tradeoffs, evaluating model outputs, and crafting high-quality design documents and specifications. Apply for a match to projects that fit your profile.

Qualifications

• 4+ years writing technical design docs, data pipelines, or API specs.
• Direct experience evaluating model outputs and documenting tradeoffs.
• Expert-level docs, spreadsheets, and slides with strong written communication.

Skills

4+ years design docs

Model evaluation & tradeoffs

Expert documentation & communication

Job description

Pay

$80/hr

The rate in the listing.

?

From the Ethos listing, checked Nov 4.

Listed

Today

Qualifications

How long hiring takes Across the platforms we list, people typically hear back about a hire within

• 4+ years as a software engineer, data engineer, or AI/ML practitioner writing technical design documents, data pipeline documentation, or API specifications
• 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
• Direct experience evaluating model outputs or system readiness and documenting technical tradeoffs for engineering or cross-functional stakeholders
• Expert-level document, spreadsheet, and slide craftsmanship, with excellent written communication and attention to detail
• Expert-level document, spreadsheet, and slide craftsmanship, with excellent written communication and attention to detail

Compensation

$80/hour

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

Location: Fully remote, work on your own schedule

Start date: ASAP

about

• 25 days of applying.
• Within 2 weeks ~30%
• Within 6 weeks ~65%
• Within 3 months ~85%

Prepare for the Ethos call

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

How do you approach designing a system when the requirements are still likely to change?

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. Over-engineering flexibility everywhere just adds complexity to parts of the system that was never going to change.

What's your process for debugging an issue that only reproduces in production, not locally?

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. I avoid making speculative changes without first confirming where the divergence is.

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

Skills and categories

• No Degree Required

Common questions

Do I need to keep applying for projects on Ethos?

No. 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.

How and when does Ethos pay experts?

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?

Between 5 and 20 hours a week. At $80/hr that is $400 to $1,600 a week. You set your own hours.

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; and expert‑level document, spreadsheet, and slide craftsmanship, with excellent written communication and attention to detail. Ethos's interviewer builds your profile from your CV, so have the roles that show this ready to talk through.

What specific skills does this listing call for?

Coding is named directly in the listing. If you don't have hands‑on experience with this, expect the screening to test for it.

How much does this specific role pay?

This listing is posted at $80/hr, an hourly rate. Pay can change after we check the listing, so confirm the rate on the platform's application page.

What happens when I click Apply on this listing?

The link opens Ethos's sign-up. There is no form for this listing: 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. Keep your CV open and cover the experience the Qualifications above ask for.

Who built Ethos and is it legitimate?

Yes. Ethos was founded in London in 2024 by James Lo (McKinsey, SoftBank Vision Fund) and Daniel Mankowitz (Google DeepMind research scientist and lead author of AlphaDev). 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. The link on this page is an affiliate link; it doesn't affect your pay or the projects you're offered.