Software Developer Expert
Ethos • Remote
Education
Not stated
Type
Hourly
Pay
$80/hr
The rate in the listing.
Listed
8d ago
Checked
- 4+ years as a software engineer, data engineer
- Direct experience evaluating model outputs or system readiness and documenting technical tradeoffs
- Expert-level document, spreadsheet, and slide craftsmanship, with excellent written communication
About this role
From the Ethos listing
About This Opportunity
We're working with a leading foundational AI lab to find experienced software developers who can help train their latest language model on professional document, spreadsheet, and slide deck tasks.
We're looking for software developers with 4+ years building software, AI/ML systems, or data infrastructure in a professional 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.
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
Qualifications
- 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
- Expert-level document, spreadsheet, and slide craftsmanship, with excellent written communication and attention to detail
How long hiring takes
On the platforms we refer people to, half of hires came within about 25 days of applying. Time from applying to hire:
Prepare for the Ethos call
Ethos's AI interviewer asks about your Educational Software Developer background. These are our own practice questions for that work, not Ethos's.
How do you design a learning interface that works for both a first-time user and a returning student who wants speed?
I design a default path with clear guidance for new users, then let usage patterns unlock shortcuts, like keyboard navigation or skip-ahead options, once the system detects familiarity. Onboarding and efficiency are different needs, so I avoid forcing every session through the same slow first-time flow.
What signals do you use to decide when an adaptive learning system should increase or decrease difficulty?
I look at response accuracy over a rolling window rather than a single answer, combined with response time, since a fast wrong answer suggests guessing while a slow wrong answer suggests a real gap. Adjusting on a single data point causes the system to feel erratic to the learner.
How do you keep educational content aligned with a curriculum standard while still allowing content authors flexibility?
I tag content against the standard at the objective level rather than the lesson level, so authors can restructure lessons freely as long as each objective is still covered somewhere. A rigid one-to-one mapping between lessons and standards breaks the moment a curriculum team wants to reorganize material.
What's your approach to testing whether an adaptive algorithm is actually improving learning outcomes, not just engagement metrics?
Engagement and learning can diverge, so I run controlled comparisons against outcome measures like retention on delayed assessments, not just time on task or completion rate. A feature that increases engagement but doesn't move outcomes needs a different justification before it ships.
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Common questions
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.
Is Ethos regular AI training work like rating chatbot responses?
No. Ethos is an expert network. AI labs, investment funds and large companies pay for your domain knowledge (deal analysis, clinical reasoning, legal logic, financial modeling) in three formats: multi-week consulting engagements, 30 to 60 minute advisory calls, and research surveys. Listings like this one are the AI-lab engagements, where you write or review expert material for a model.
How many hours a week is this Software Developer 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 Developer 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.