AI Engineer Expert
Ethos • Remote
Education
Not stated
Type
Hourly
Pay Rate
$100/hr
Listed
141d ago
Apply opens Ethos in a new tab.
Apply Now → ⚡ Boost your chances - Optimize your resume with Rezi.aiAbout this role
From the Ethos listing
Ethos's AI Engineer opening pays $100/hour and wants 3+ years building production AI systems or LLM-powered applications, with real experience in LLM integration, RAG pipelines, or evaluation frameworks. The work is reviewing AI-generated code and system design for correctness and reliability at the level a working AI engineer would apply to a production pull request. It's remote and flexible, one of Ethos's steadier STEM roles filled through referral.
Requirements
- Must be eligible to work in Remote
- Fluent proficiency in English (Written & Verbal)
- Reliable high-speed internet connection
- Bachelor's degree or equivalent professional experience
- Demonstrated expertise in Software Engineering
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Interview Prep
Sample questions for a AI Engineer role, written in-house to help you prepare.
How do you decide which evaluation metric to optimize for a classification model when the classes are imbalanced?
Accuracy is misleading on imbalanced data because a model can score well by always predicting the majority class. I look at precision, recall, and F1 for the minority class specifically, and pick the metric that matches the real cost of false positives versus false negatives in the deployment context, since those costs are rarely symmetric in practice.
What is your process for debugging a deep learning model that trains fine but performs poorly at inference time?
I start by checking for a train/inference mismatch: different preprocessing, batch normalization behaving differently in eval mode, or data leakage during training that inflated validation scores. Comparing the exact input pipeline used at training time against the one used at inference usually surfaces the discrepancy before I need to touch the model architecture itself.
How do you approach feature selection when working with high-dimensional tabular data?
I start with correlation and mutual information analysis to drop obviously redundant features, then use a tree-based model's feature importance as a first pass filter. From there, recursive feature elimination with cross-validation tells me where the marginal value of additional features drops off, which keeps the final feature set both smaller and more robust to overfitting.
Explain how you would detect and address data drift in a production machine learning pipeline.
I monitor the statistical distribution of input features and model outputs over time, using something like population stability index or KL divergence against a reference window. When drift crosses a threshold, I retrain on recent data rather than the full historical set, and I keep an alert in place so drift is caught before it shows up as a quality regression.
Why this role
This AI Engineer Expert role pays $100/hr for your Software Engineering judgment directly, without requiring case files, client meetings, or firm overhead to get there.
Skills and categories
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Common questions
How and when does Ethos pay experts?
Within 30 days of invoice submission after a project closes. That net-30 schedule is standard for enterprise expert networks, but it's slower than the weekly payouts some AI training platforms offer, so plan your cash flow around it.
Is Ethos regular AI training work like rating chatbot responses?
No. Ethos is an expert network, not a task queue. AI labs, investment funds, and Fortune 500s pay to access your specific domain knowledge (deal analysis, clinical reasoning, legal logic, financial modeling) through three formats: multi-week consulting engagements, 30-60 minute advisory calls, and targeted research surveys.
Is AI training work the same as traditional consulting?
No. Instead of client deliverables, you're given complex scenarios to evaluate: grading the AI's logic, correcting its hallucinations, and supplying expert-level reasoning it doesn't have on its own. The job is closer to teaching than consulting.
Why do these AI training roles pay so much?
Because general knowledge isn't what's being tested. The model already knows the basics; what it needs is expertise on edge cases, the rare, difficult, highly technical judgment calls only a senior professional in the field would make correctly.
What does Software Engineering work look like for an AI Engineer Expert?
Tasks here are scoped to Software Engineering, not generic labeling. As an AI Engineer Expert, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Software Engineering) rather than following a one-size-fits-all rubric. If you don't have hands-on Software Engineering background, this is likely not the right listing to start with.
What specific skills does this listing call for?
Coding and Expert are named directly in the listing. If you don't have hands-on experience with these, expect the screening process to test for them directly rather than accepting adjacent experience as a substitute.
How much does this specific role pay?
This listing is posted at $100/hr, an hourly rate. Pay can change between when we last checked the listing and when you apply, so confirm the current number on the platform's own application page before committing time.
What happens when I click Apply on this listing?
You'll be taken to Ethos's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.
Who built Ethos and is it legitimate?
Yes, it's legitimate and well-funded: Ethos raised $3.5M from General Catalyst and was co-founded by Daniel Mankowitz (Google DeepMind research scientist and lead author of AlphaDev) and James Lo (McKinsey, SoftBank Vision Fund). Over 17,000 experts have signed up, and it's actively working with 25+ PE firms, hedge funds, and consultancies. The referral link on this page is an affiliate link; it doesn't affect your pay or opportunities.