micro1 and Turing both run AI-led interviews, both pay reasonably well, and both place contractors with AI labs and enterprise customers. They're also genuinely different products under the surface. micro1 started life as an AI-training-focused platform with broad coverage across generalist evaluation, SME work, and technical roles. Turing began as a remote-engineering marketplace and scaled its AI-training arm aggressively starting in 2023 — the platform still skews heavily toward software-engineering and code-evaluation work.
This is the honest comparison: where each one wins, where they overlap, and which to apply to first depending on your background.
TL;DR — the verdict
- micro1 is broader. Generalist eval, SME tasks, coding, writing, analyst-style work. Typical pay $40–$90/hr; high end ~$150/hr.
- Turing is engineering-deeper. Heavy emphasis on code generation, code review, and software-engineering evaluation work. Typical pay $40–$100+/hr; senior-engineering roles ($90–$150/hr) are more common than on micro1.
- Turing's application tests coding. Expect a coding screen, often through a take-home or live problem in addition to the conversational AI interview. micro1's interview is more conversational.
- micro1 has lower friction for non-engineers. Faster onboarding, broader acceptance, more roles for generalists and SMEs.
- Run both if you write code professionally. Neither has exclusivity. Strong engineers get the highest total earnings by running both and picking whichever engagement is paying best.
Pay: where the dollars actually land
micro1
micro1's pay scales horizontally — most roles fall in $40–$90/hr, with a long tail up to $150/hr for senior engineering and specialized expert work. The floor is higher than commodity annotation platforms (very few sub-$30/hr roles), but the ceiling is lower than Mercor's domain-expert peak. Payment is weekly via Wise or Stripe.
Turing
Turing's pay skews higher for engineering work. Software engineering and code-evaluation roles cluster in $60–$120/hr; senior-engineering placements (FAANG-equivalent backgrounds) push into $130–$150+/hr. Non-engineering roles exist but are a smaller share of the catalog and tend to pay $40–$80/hr. Payment is typically biweekly via Wise, ACH, or wire depending on geography.
Per-hour vs total earnings
The same caveat as every platform comparison: hourly rate isn't everything. A Turing placement at $110/hr that gives you 12 hours/week earns less than a micro1 placement at $75/hr that gives you 25 hours/week. Sustained-hours visibility tends to be better on micro1 (broader catalog → more roles available at any moment). Turing engagements tend to cluster around specific clients and can be more all-or-nothing.
Job types: where they actually overlap and diverge
micro1's core competency: broad contractor placement
micro1 places contractors across a wide band — from generalist evaluation work (any educated adult with strong writing skills) up through senior engineering and specialist expert roles. Typical engagements:
- Generalist RLHF preference labeling on conversational AI
- Code generation evaluation across mainstream languages
- Analyst-style data work — review, summarization, fact-checking
- SME tasks across business, science, and professional domains
- Long-running engagements where the same contributor sticks with a client for months
Turing's core competency: engineering-heavy AI training
Turing's AI training arm was built on top of its existing engineer marketplace, and the catalog reflects that. Typical engagements:
- Code generation evaluation — judging correctness, style, edge-case handling
- Code-review work on model-generated PRs in real codebases
- Specification writing for coding tasks the lab will then train on
- Stack-specific expert evaluation (e.g. Rust systems work, ML frameworks, distributed systems)
- Reasoning evaluation for agentic / tool-using coding models
Translation: if you're a software engineer, Turing has more roles that target your background specifically, at higher rates. If you're not an engineer, Turing has fewer roles for you and they tend to pay less than the equivalent on micro1.
Application process: what to expect
micro1
Résumé upload → AI-led interview, typically 15–30 minutes, conversational rather than depth-probing. The bar is lower than Mercor's; most reasonable applicants with verifiable credentials get through. Once accepted, you see available roles and can apply to specific ones rather than waiting for Mercor-style placement.
Turing
Two-stage. First, an AI-led conversational interview similar to micro1's in length. Second, for engineering roles, a coding evaluation — usually a take-home problem (1–3 hours of work) or a live problem-solving session. Both stages must clear before you're placed. The coding screen is the real filter; conversational polish without the code chops won't get you in for engineering roles.
For interview tactics that apply to both platforms (and to the AI-led format in particular), see our AI training interview guide.
Which one should you apply to first?
- You're a software engineer (any seniority) → Turing first, then micro1 in parallel. Turing's rates for engineers are higher and more roles fit your background. Apply to micro1 as well to broaden where you can land work.
- You're a senior engineer (FAANG-equivalent, 5+ years) → Turing AND consider Mercor too. The Mercor vs micro1 piece covers Mercor's positioning if you have senior credentials.
- You're a strong generalist, not an engineer → micro1 first. Turing has roles for you but fewer of them and at lower rates. micro1's catalog will surface more options.
- You're an SME outside engineering (medical, legal, finance, sciences) → micro1 first; then look at Mercor and the broader platform list. Turing's SME catalog is thinner.
- You're early-career without an engineering portfolio → micro1. Turing's coding screen filters out applicants without a real codebase or repo history to point at.
Can you run both at the same time?
Yes. Neither has platform-level exclusivity. Top-earning engineers in this space routinely carry both: micro1 as a stable income floor (broader catalog → easier to find available roles), Turing for higher-paying specialized engagements when the right thing opens up.
Operationally: track hours separately, expect a 1099-NEC from each, and check per-engagement NDA / non-compete language — sometimes individual engagements restrict competitive work for specific clients, even if the platforms don't.
The honest weakness of each
micro1's downside
Engineering rates plateau lower than Turing's. If you're a senior engineer who could clear Turing's coding screen, you'll likely earn more there per hour than on micro1.
Turing's downside
Narrower fit. The coding-screen requirement filters out a lot of otherwise-strong contributors. If you don't write code professionally, you're applying for a smaller slice of Turing's catalog, often at unimpressive rates.
How to actually apply to both efficiently
Submit both on the same evening. Use the same résumé. micro1's interview is faster (15–30 min); Turing's pipeline is longer because of the coding screen (1–3 hours of take-home plus the conversational interview). The two platforms don't share data, so each evaluates independently.
For pay-tier context across the broader market, see our AI training pay breakdown, or for an engineer-specific deep dive, the AI training jobs for engineers guide covers Turing in more detail alongside the other engineer- heavy platforms.