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Machine Learning Data Linguist Jobs (NOW HIRING)

Welocalize, Inc.

Data Quality Lead

New York, NY

... Linguistics or a related field. Experience: * Prior experience in a leadership role within a data annotation or machine learning team. * Proven track record of team management, mentorship, and ...

Welocalize, Inc.

Data Quality Lead

San Francisco, CA

... Linguistics or a related field. Experience: * Prior experience in a leadership role within a data annotation or machine learning team. * Proven track record of team management, mentorship, and ...

Twilio

Principal Machine Learning & Data Engineer

$138K - $185K/yr

About the job Twilio's next L5 Machine Learning & Data Engineer to lead the design, build, and operation of the internal ML-and-data platform that powers every customer interaction. You will ...

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Machine Learning Data Linguist information

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$52K

$73.4K

$95.5K

How much do machine learning data linguist jobs pay per year?

As of Jun 20, 2026, the average yearly pay for machine learning data linguist in the United States is $73,373.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,500.00 and $79,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Data Linguist, and why are they important?

To thrive as a Machine Learning Data Linguist, you need expertise in linguistics, data annotation, and a strong understanding of language structures, often supported by a degree in linguistics or computational linguistics. Familiarity with annotation tools, data labeling platforms, and programming languages like Python is typically required. Strong attention to detail, analytical thinking, and clear communication are essential soft skills for accurately interpreting and conveying linguistic phenomena. These skills ensure high-quality language data, which is critical for developing effective and unbiased machine learning models.

What is a Machine Learning Data Linguist?

A Machine Learning Data Linguist is a specialist who works at the intersection of linguistics and artificial intelligence. They are responsible for annotating, curating, and analyzing language data to train and improve machine learning models, especially those focused on natural language processing (NLP). Their work often includes tasks like labeling text, refining speech recognition data, and ensuring that language models understand context, grammar, and cultural nuances. This role is essential in developing accurate and inclusive AI systems that interact with human language.

How does a Machine Learning Data Linguist typically collaborate with engineers and data scientists on projects?

A Machine Learning Data Linguist works closely with engineers and data scientists by providing linguistic insights and ensuring that language data is accurately annotated and interpreted. They often participate in cross-functional meetings to define project goals, clarify annotation guidelines, and review model outputs for linguistic quality. This collaboration helps bridge the gap between technical development and language-specific nuances, leading to more effective and culturally accurate machine learning models. Effective communication and a strong understanding of both linguistic theory and technical requirements are vital in this collaborative environment.
More about Machine Learning Data Linguist jobs
What cities are hiring for Machine Learning Data Linguist jobs? Cities with the most Machine Learning Data Linguist job openings:
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Machine Learning Data Linguist jobs near you
Infographic showing various Machine Learning Data Linguist job openings in the United States as of June 2026, with employment types broken down into 5% Internship, 84% Full Time, and 11% Contract. Highlights an 100% In-person job distribution, with an average salary of $73,373 per year, or $35.3 per hour.
Data Quality Lead

Data Quality Lead

Welocalize, Inc.

New York, NY

Full-time

Posted 4 days ago

Welocalize rating

5.9

Company rating: 5.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

335th of 428 rated business services

Job description

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Job Responsibilities:

The ideal candidate will possess both technical prowess in machine learning and natural language processing, along with strong leadership skills to guide and mentor their team.

Key Responsibilities:

Team Leadership and Management:

  • Lead, mentor, and grow a team of data annotators and quality analysts.
  • Ensure team members are trained, informed, and adhere to company standards and best practices.
  • Oversee team performance, set goals, and conduct regular evaluations.

Strategic Oversight:

  • Collaborate with senior management to define strategic goals and deliverables.
  • Allocate resources and tasks efficiently among team members.
  • Act as a bridge between the annotation team and other departments, ensuring effective communication.

Quality Assurance and Analysis:

  • Oversee quality assurance processes and set benchmarks for performance and accuracy.
  • Review and approve detailed reports on findings prepared by team members.
  • Drive continuous improvement initiatives within the team based on analytics and performance metrics.

Technical Expertise:

  • Stay updated with the latest in machine learning, data annotation, and natural language processing.
  • Address complex technical challenges faced by the team.
  • Provide guidance on advanced annotation techniques and quality analysis.

Linguistic and NLP Leadership:

  • Guide the team in applying best practices in NLP and linguistics.
  • Ensure consistent linguistic accuracy across all processed and annotated data.

Education: Bachelor's degree in Computer Science, Data Science, Linguistics or Computational Linguistics or a related field.

Experience:

  • Prior experience in a leadership role within a data annotation or machine learning team.
  • Proven track record of team management, mentorship, and performance optimization.
  • Strong analytical skills with the ability to derive actionable insights from data.
  • Deep understanding of machine learning models, data annotation, and quality assurance.
  • Excellent communication and interpersonal skills.

Additional Job Details:

Additional Information:

This role primarily focuses on English US data sets; however, having experience with translation or multi-lingual data sets can be advantageous.

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