AlignerrCoding & software eval
Environmental Engineering
up to $60/hr
About this role, in Alignerr's words
We're partnering with the world's leading AI research teams to build smarter, more technically rigorous AI models — and we need environmental engineers to help get it right.
What you'll do
- Design Complex Problems — Create advanced environmental engineering challenges spanning contaminant transport, mass balances in treatment plants, hydrology, air dispersion modeling, and Life Cycle Assessments (LCA)
- Author Ground-Truth Solutions — Develop rigorous, step-by-step reference solutions including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations that serve as the benchmark for AI evaluation
- Audit AI Outputs — Review AI-generated remediation plans, environmental impact statements, and engineering calculations for technical accuracy, safety, and regulatory compliance (EPA, ISO 14001, and others)
Show all 5 itemsHide the other 2 in What you'll do
- Sharpen AI Reasoning — Identify and document model failures such as incorrect stoichiometry, flawed mass balance logic, or failure to account for secondary environmental impacts, then provide structured feedback to correct them
- Work Independently — Take ownership of tasks and complete them asynchronously on a schedule that works for you
Candidate background
Who You Are
- Pursuing or holding a Master's or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related discipline
- Strong foundational knowledge in one or more of: aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation
- Able to communicate complex technical and ecological concepts clearly and precisely in writing
- Meticulous about unit conversions (mg/L to ppm, etc.), chemical equations, and regulatory logic
- Self-directed and comfortable working on independent, task-based assignments
- No prior AI experience required
Nice to Have
Show all 3 itemsHide these 3 items in Nice to Have
- Experience with data annotation, quality evaluation, or technical review processes
- Familiarity with environmental modeling software (e.g., AERMOD, SWMM, MODFLOW)
- Background in EHS compliance or environmental consulting
Quoted from selected sections of Alignerr's posting. The full posting may state other conditions. Read the full posting
A closer look
More context, when you need it.
Full job descriptionThe original posting, in Alignerr's words
Posted by Alignerr, reproduced here so you can judge the role before clicking. Original posting ↗
Environmental Engineering — AI Data Trainer
About the Role
We're partnering with the world's leading AI research teams to build smarter, more technically rigorous AI models — and we need environmental engineers to help get it right.
This is a unique opportunity to apply your deep expertise in water treatment, air quality, remediation, and environmental compliance to a problem that matters: making sure AI reasons correctly about the physical and chemical world. You'll stress-test advanced language models, expose their blind spots, and help train the next generation of AI to think like an expert.
If you've ever wanted to work at the cutting edge of AI without leaving your field, this is it.
- Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week
What You'll Do
* Design Complex Problems — Create advanced environmental engineering challenges spanning contaminant transport, mass balances in treatment plants, hydrology, air dispersion modeling, and Life Cycle Assessments (LCA) * Author Ground-Truth Solutions — Develop rigorous, step-by-step reference solutions including chemical dosage calculations, hydraulic flow models, and pollutant dispersion simulations that serve as the benchmark for AI evaluation * Audit AI Outputs — Review AI-generated remediation plans, environmental impact statements, and engineering calculations for technical accuracy, safety, and regulatory compliance (EPA, ISO 14001, and others) * Sharpen AI Reasoning — Identify and document model failures such as incorrect stoichiometry, flawed mass balance logic, or failure to account for secondary environmental impacts, then provide structured feedback to correct them * Work Independently — Take ownership of tasks and complete them asynchronously on a schedule that works for you
Who You Are
* Pursuing or holding a Master's or PhD in Environmental Engineering, Civil Engineering (environmental focus), or a closely related discipline * Strong foundational knowledge in one or more of: aquatic chemistry, wastewater process design, air quality engineering, or hazardous waste remediation * Able to communicate complex technical and ecological concepts clearly and precisely in writing * Meticulous about unit conversions (mg/L to ppm, etc.), chemical equations, and regulatory logic * Self-directed and comfortable working on independent, task-based assignments * No prior AI experience required
Nice to Have
* Experience with data annotation, quality evaluation, or technical review processes * Familiarity with environmental modeling software (e.g., AERMOD, SWMM, MODFLOW) * Background in EHS compliance or environmental consulting
Why Join Us
* Work on genuinely interesting, intellectually demanding problems that push your expertise * Fully remote and flexible — work when and where you choose * Collaborate with a global team contributing to cutting-edge AI research * Get hands-on exposure to how large language models are trained and evaluated * Freelance autonomy with the opportunity for ongoing, extended engagement
Working with AlignerrPay, getting started and work, from Alignerr's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Billed weekly, Monday to Sunday, with approved work paid by the following Friday, according to Labelbox's help center. Payment goes through Stripe Connect or PayPal depending on your location, with one provider per country. intercom.help/labelbox/en/articles/13600616-alignerr-paym..., alignerr.com/process
- Before your first paid task
- Sign up, apply, verify your identity, set up billing and onboard. Some jobs add a Zara AI interview or domain assessments. alignerr.com/process
- How much work
- Time to your first project depends on demand and your skills, and there is no minimum number of hours. alignerr.com/faqs
- Contract
- Independent contractor, under terms with ALIGNERR LLC. alignerr.com/faqs, alignerr.com/privacy
Read on the pages linked above on 24 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
How does the pay compare?Across Coding & software eval roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from Alignerr's posting. How we count.
Pay across the field: Coding & software eval
Across 393 roles in this field with a stated hourly rate in US dollars, on 14 platforms, the middle half pays $65 to $120 an hour at the top of the range, and the median is $95. This role's top rate, $60, is in the bottom quarter. Of the 141 distinct rates we count, 26 are lower and 108 are higher.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Alignerr (this platform) | 136 | $50 to $400 · median $100 |
| micro1 | 46 | $35 to $350 · median $110 |
| Handshake AI | 43 | $47 to $125 · median $80 |
| Meridial (Invisible) | 34 | $22 to $150 · median $60 |
| Mercor | 33 | $60 to $200 · median $105 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 27 Aug 2026, and still on Alignerr's list when we last read it on 13 Oct 2026.
- The listed pay has not changed since then.
- Posted by Alignerr
- First seen by AIPayList
- Last seen live
- Listing ID
- 31fe200a-e116-41ec-8cb8-05f31f8d8343
Pay as the source states it: “$35-60/hr”.
Alignerr posts this role once per country: 2 listings with the same title and pay. We treat them as one role, open in 0 countries.
Platforms sometimes change a rate after posting. Every listing here is re-read at least once a day and corrected when its source moves, so a difference you see on the platform is usually a change made since the last read. How freshness works.
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