SME Careers Is Hiring Quality Assurance Leads (QAL) Across 70+ Domains [June 2026]
SME Careers asked us to help source Quality Assurance Lead (QAL) candidates with 6+ months of AI data experience, across 70+ domains. If you have led QA, managed queues, or coordinated projects at an AI data company, you probably already qualify. Here are the roles, the pay, and how to apply.
SME Careers (the AI data services arm of SuperAnnotate) reached out to us directly and asked for help finding candidates for their open Quality Assurance Lead (QAL) roles: people with at least 6 months of experience at an AI data company who can audit AI training output, review contributor work, and keep quality high across a project. They have openings across more than 70 domains, from Python and Legal to 35+ languages.
Here is the part most people miss: your job title probably is not "QAL." SME is hiring experienced quality and operations people from across the AI data industry, and the same work goes by a dozen different names. If you have done this work anywhere, this guide shows you exactly which role to apply to and how.
You Probably Already Qualify
That includes anyone who has spent time at a company doing LLM training, AI data annotation, AI evaluation, RLHF, or related AI operations. If you have worked at any of these, you are exactly who they want:
The same job has many titles
If you worked similar positions at other platforms, your job title may not have necessarily been "Quality Assurance Leader." SME is hiring operations people from across the AI data industry, so if you have held any of these titles, or done the equivalent work, you qualify:
What ties all of these together is the actual work: leading quality initiatives, auditing outputs, reviewing contributor work, developing guidelines, managing workflows, and overseeing quality processes on AI training and evaluation projects. If that describes your last role, keep reading.
What a Quality Assurance Lead Actually Does
A QAL is the quality backbone of an AI training project. You are not producing the raw data yourself; you are making sure everyone else's output is accurate, consistent, and aligned with the client's guidelines. Across the listings, the responsibilities are remarkably consistent:
Core Responsibilities
- → Spot-check items, identify quality issues, and escalate critical ones
- → Review AI-generated output and contributor work against the rubric
- → Write precise, actionable feedback for trainers and QAs
- → Maintain style guides, trackers, FAQs, honeypots, and calibration tasks
- → Run onboarding and training calls for new contributors
What Makes You Competitive
- ✓ Deep expertise in the specific domain (the language, the code, the field)
- ✓ Strong written English for clear technical feedback
- ✓ Experience leading or coordinating remote contributor teams
- ✓ Comfort with Discord, Google Sheets, trackers, and dashboards
- ✓ Prior AI training, annotation, or rubric-based review work
Specialist QAL Roles ($90 to $120/hr)
The top of the pay scale goes to roles that need a hard-to-replace professional background: a working data scientist, a practicing lawyer, a licensed clinician. These are the QAL roles where domain depth is non-negotiable, and where the smallest pool of qualified people competes.
STEM & Engineering QAL Roles
The engineering and hard-science QALs pay $75 to $105/hr and reward an actual degree or professional track record in the field. The four engineering disciplines sit at the top of this band at $105/hr.
Software & Coding QAL Roles
If you are a developer who can read code critically and explain why an implementation is wrong, the coding QALs pay $65 to $80/hr. You will review AI-generated code, debugging responses, and explanations for correctness, idiom, and clarity. HTML/CSS leads the band at $80/hr.
Kotlin, Dart, R, and Bash QALs are also open, up to $65/hr each. See all coding QAL roles →
Language QAL Roles
The largest group by far: more than 35 language QAL roles. You will review multilingual AI training data for fluency, cultural accuracy, and adherence to guidelines, and lead a team of native-speaker contributors. Pay varies by language and region, from $20/hr up to $60/hr for the highest-demand European languages.
Higher band · $50 to $60
Middle band · $30 to $45
Entry band · $20 to $25
- Vietnamese · $25
- Indonesian · $25
- Filipino / Tagalog · $25
- Thai · $25
- Tamil · $20
- Urdu · $20
- Bengali · $20
That is a sample. There are 35+ language QALs in total, including Turkish, Persian, Ukrainian, Romanian, Czech, Hungarian, Slovak, Bulgarian, Croatian, and several Indian languages (Tamil, Telugu, Kannada, Marathi, Malayalam, Gujarati, Punjabi, and more).
Pay by Domain
QAL pay tracks the scarcity of the expertise, not the difficulty of the QA work itself. Here is the full spread, highest to lowest:
| Domain | Roles | Pay (up to) |
|---|---|---|
| Data Science | Python ML, Data Scientist | $120/hr |
| Legal | Legal QAL | $120/hr |
| Engineering (STEM) | Biomedical, Civil, Chemical, Electrical, Mechanical | $105/hr |
| Healthcare | Medical QAL | $95/hr |
| Finance / Accounting | Financial, Excel | $90/hr |
| Science / Math | Biology, Chemistry, Mathematics | $75/hr |
| Software Engineering | HTML/CSS, C/C#/C++, Java, JS, TS, Go, and more | $80/hr |
| Languages | 35+ language QALs | $20 to $60/hr |
Rates are the listed ceilings. Your actual pay depends on your location and local market conditions; SME confirms the specific rate during the application process.
What to Expect
A few logistics worth knowing before you apply:
- Open globally, no location restriction. SME is hiring for these roles regardless of where you live.
- Most are talent-pool roles, not immediate openings. There may be no project running the day you are accepted. SME builds a vetted expert pool and reaches out first when a matching project opens, so applying now puts you at the front of that line and gives you access to future work too.
How to Apply and Stand Out
The selection process is consistent across the QAL roles: an AI interview, a domain-specific task, and an interview with a recruiter. To get through it, lead with the quality and operations work, not just your domain credential.
Translate your title into QAL language
If you were a Queue Manager or Project Coordinator at an AI data company, say so plainly, then describe the QA work: how many contributors you reviewed, what guidelines you wrote, how you caught and escalated quality issues.
Show the 6 months of relevant experience
SME's bar is at least 6 months in a similar role at an LLM training, annotation, evaluation, or RLHF company. Name the platform and the project type. Familiar names (Scale, Surge, Outlier, Mercor, Alignerr, Micro1, Invisible) signal instantly.
Prove your written feedback is clear
The whole job is precise written feedback against a rubric. Treat the domain task as a writing sample: be specific, structured, and unambiguous about why an output passes or fails.
New to AI evaluation work and want to build the credential first? Our AI Trainer Certification covers the quality and evaluation fundamentals these roles assume.
See Every Open QAL Role
This guide covers the headline roles. To browse all 70+ Quality Assurance Lead openings on SME Careers, filter by domain, and check the live pay for each one, use the board below.
Explore All SME Careers Jobs
Weekly (via Deel)
QAL roles are just part of it. See every open SME Careers listing and filter by domain, skill, and pay rate.
Related guides
SME Careers full review — pay, legitimacy, and the full contractor experience.
SME Careers application & assessment guide — how to pass the screening.
Browse live SME Careers jobs — every open role, updated regularly.
How to find AI training jobs — where the work is and how to land it.
Pietro R.
MSc Human-Computer Interaction | Founder & Product Owner
Pietro is the founder and technical lead of aitrainer.work. He builds and maintains the platform's data pipeline, certification infrastructure, and editorial standards.