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Language Annotator Jobs (NOW HIRING)

LILT, Inc

Production Manager, Applied AI

Boston, MA · On-site

$110K - $145K/yr

... the language they speak. We use cutting-edge AI, machine translation, and human-in-the-loop ... Repeated misses by a PM or annotator pool lead to documented remediation or replacement. Issues are ...

Verantos

Senior Product Manager

$129K - $170K/yr

Working knowledge of natural language processing (NLP), machine learning (ML), and the concepts behind model training, evaluation, and accuracy measurement (precision, recall, F1, inter-annotator ...

Cyborg Mobile

Data & AI Program Manager

Redmond, WA · On-site +1

... that fuels natural language processing (NLP) applications and large language model (LLM ... Strong understanding of data annotation workflows, guideline design, and inter-annotator quality ...

Careerflow

Japanese Data Annotator

$640/wk

Job Title We are looking for native or fluent language speakers to help train AI systems by reviewing and annotating content in their language. This is a long-term, remote gig. No prior experience is ...

Cyborg Mobile

Data & AI Program Manager

Redmond, WA · On-site +1

... that fuels natural language processing (NLP) applications and large language model (LLM ... Strong understanding of data annotation workflows, guideline design, and inter-annotator quality ...

Jobless

Instrument model quality monitoring in production -- detecting degradation across language pairs ... annotator agreement analysis -- with statistical rigor. * Strong engineering skills: you can build ...

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Language Annotator information

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$32K

$44.1K

$51K

How much do language annotator jobs pay per year?

As of Sep 13, 2026, the average yearly pay for language annotator in the United States is $44,079.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,500.00 and $50,000.00 per year, depending on experience, location, and employer.

What is a language annotator?

Language Annotators are professionals who label, categorize, and tag text, audio, or speech data to help train and improve natural language processing systems and AI models. Their work involves identifying linguistic features such as parts of speech, named entities, sentiment, or intent in language data. Language Annotators play a crucial role in making AI technologies like chatbots, translation tools, and voice assistants more accurate and effective. They often work with large datasets and follow specific guidelines to ensure consistency and quality in the annotations.

What skills and qualifications are needed to thrive as a language annotator?

To thrive as a Language Annotator, you need strong linguistic knowledge, attention to detail, and typically a background in linguistics or a related field. Familiarity with annotation tools, text analysis software, and version control systems like Git is often required. Excellent communication, critical thinking, and the ability to follow detailed guidelines are essential soft skills. These skills ensure the production of high-quality, consistent data crucial for training effective language models and supporting NLP research.

What are common challenges faced by language annotators, and how can they be managed?

Language Annotators often encounter challenges such as maintaining consistency in annotation, managing large volumes of data, and adapting to evolving guidelines. To address these, it's important to communicate regularly with team members, participate in calibration sessions, and seek clarification when guidelines are unclear. Utilizing annotation tools efficiently and staying organized can also help manage workload and ensure high-quality results.
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What are popular job titles related to Language Annotator jobs?

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Language Annotator jobs near you
Infographic showing various Language Annotator job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 74% Full Time, 19% Part Time, 1% Temporary, and 5% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $44,079 per year, or $21.2 per hour.

Production Manager, Applied AI

Boston, MA • On-site

LILT, Inc
Translation Services • 51 - 200 employees
Learn more about LILT, Incexternal

$110K - $145K/yr

Full-time

Posted 12 days ago

Key responsibilities

  • Manage the performance of projects by ensuring on-time delivery, quality, and cost targets are met, and review progress regularly.

  • Oversee the hiring, onboarding, and development of project managers to maintain adequate capacity and program start timelines.

  • Implement quality interventions across programs by monitoring for quality issues, conducting QA loops, and initiating corrective actions.

Job description

About LILT
AI is changing how the world communicates - and LILT is leading that transformation.
We're on a mission to make the world's information accessible to everyone, regardless of the language they speak. We use cutting-edge AI, machine translation, and human-in-the-loop expertise to translate content faster, more accurately, and more cost-effectively without compromising on brand, voice, or quality.
At LILT, we empower our teammates with leading tools, global collaboration, and growth opportunities to do their best work. Our company virtues-Work together, win together; Find a way or make one; Dance in the customer's shoes; Quicker than they expect; Quality is Job 1-guide everything we do. We are trusted by Intel Corporation, Canva, the United States Department of Defense, the United States Air Force, ASICS, and hundreds of global Enterprises. Backed by Sequoia, Intel Capital, and Redpoint, we're building a category-defining company in a $50B+ global translation market being redefined by AI.
Key Responsibilities
  • PM Performance
    • Outcome: Every active program has accountable Project Manager(s), and every PM carries a workload within the agreed span. Programs hit on-time delivery and first-pass acceptance targets without escalation; each PM is reviewed monthly against a scorecard of throughput, quality, and cost-per-task.
  • PM Hiring, Onboarding, and Development
    • Outcome: PM pool capacity keeps pace with signed demand: new PMs are sourced, onboarded, and running their first program within the agreed ramp window, all programs start on time, and PM attrition is below threshold.
  • Quality Interventions Across Programs
    • Outcome: Quality dips are caught mid-program through QA loops and corrected via retraining of annotator pools or guideline updates. Repeated misses by a PM or annotator pool lead to documented remediation or replacement. Issues are proactively discovered.
  • Process Standardization & Software Improvements
    • Outcome: Programs launch from shared playbooks, guideline templates, and dashboard standards rather than being rebuilt per engagement. Every post-mortem produces documented improvements that lead directly into our custom software stack, and time from program handoff to first delivery declines quarter over quarter.
  • Escalation and Cross-Functional Interface
    • Outcome: Risks surface to Technical Program Managers early enough to be managed. Escalations between the PM pool, Quality, Talent, and Delivery are resolved within agreed timelines.
Qualifications
  • People management in AI data operations: 5+ years in AI/ML data operations or production, including 2+ years directly managing project managers or team leads in a distributed, multi-time-zone contractor environment.
  • LLM knowledge: Strong understanding of LLM training processes (pre-training, SFT, RLHF) and evaluation methodologies (human-in-the-loop, red teaming), and of what drives quality and throughput in annotation workflows.
  • KPI-driven management: Has run teams against throughput, quality (accuracy, IAA, gold-set), and cost-per-task targets; advanced proficiency with spreadsheets and dashboards, and able to use SQL to extract and analyze performance data.
  • Delivery track record: Has sustained on-time delivery and acceptance targets across multiple concurrent data collection or evaluation programs for enterprise or research lab customers.
  • Contractor workforce operations: Has hired, ramped, performance-managed, and offboarded hourly and freelance staff across regions and languages.
  • Methodology: Proven track record using Agile, Scrum, or Kanban to manage complex workflows across a portfolio of programs.
  • Communication: Writes clear, unambiguous guidelines and feedback for multilingual audiences and communicates status, risk, and tradeoffs crisply to leadership.
Preferred Skills
  • Fluency in multiple human languages.
  • Experience with multilingual data deliveries (pre-training, SFT, RLHF, machine translation, multimodal, etc.), especially in rare-resource languages
  • Experience with data annotation platforms (e.g., Label Studio, SuperAnnotate) and project management tooling (e.g., Jira).
  • Background in ML engineering, computer science, or data science.

Where You'll Work
This position is based in our Boston office and will be expected to work in the office in a hybrid capacity. LILT is hybrid with hubs in SF, NY, Indianapolis, Boston, London, and Berlin.
Authorization to work in the U.S. is a precondition of employment.
  • Boston (highly preferred)
  • Others: SF Bay Area, New York, Indianapolis, London

Our Story
Our founders, Spence and John met at Google working on Google Translate. As researchers at Stanford and Berkeley, they both worked on language technology to make information accessible to everyone. While together at Google, they were amazed to learn that Google Translate wasn't used for enterprise products and services inside the company.The quality just wasn't there. So they set out to build something better. LILT was born.
LILT has been a machine learning company since its founding in 2015. At the time, machine translation didn't meet the quality standard for enterprise translations, so LILT assembled a cutting-edge research team tasked with closing that gap. While meeting customer demand for translation services, LILT has prioritized investments in Large Language Models, human-in-the-loop systems, and now agentic AI.
With AI innovation accelerating and enterprise demand growing, the next phase of LILT's journey is just beginning.
Our Tech
What sets our platform apart:
  • Brand-aware AI that learns your voice, tone, and terminology to ensure every translation is accurate and consistent
  • Agentic AI workflows that automate the entire translation process from content ingestion to quality review to publishing
  • 100+ native integrations with systems like Adobe Experience Manager, Webflow, Salesforce, GitHub, and Google Drive to simplify content translation
  • Human-in-the-loop reviews via our global network of professional linguists, for high-impact content that requires expert review
LILT in the News
  • Featured in The Software Report's Top 100 Software Companies!
  • LILT makes it onto the Inc. 5000 List.
  • LILT's continues to be an intellectual powerhouse, holding numerous patents that help power the most efficient and sophisticated AI and language models in the industry.
  • Check out all our news on our website.

Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to LILT's Privacy Policy at https://lilt.com/legal/privacy.
At LILT, we are committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision-making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt-out of the use of AI in our hiring process, please let us know at recruiting@lilt.com.
LILT is an equal opportunity employer. We extend equal opportunity to all individuals without regard to an individual's race, religion, color, national origin, ancestry, sex, sexual orientation, gender identity, age, physical or mental disability, medical condition, genetic characteristics, veteran or marital status, pregnancy, or any other classification protected by applicable local, state or federal laws. We are committed to the principles of fair employment and the elimination of all discriminatory practices.

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