ZipRecruiter

Log In

1

Machine Learning Data Linguist Jobs (NOW HIRING)

Extend

Senior Machine Learning Data Scientist

$135K - $165K/yr

The Fraud & Machine Learning team is the secret sauce behind Extend's post-purchase protection platform. As a Senior ML Data Scientist, you will own the development of cutting-edge machine learning ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL · On-site

$73K - $131K/yr

Position Description ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and ... Work closely with other senior scientist to understand problem sets, physical data feature sets and ...

next page

Showing results 1-20

All JobsMachine Learning Data Linguist Jobs

Machine Learning Data Linguist information

See salary details

$52K

$73.4K

$95.5K

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

As of Jul 13, 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:
What states have the most Machine Learning Data Linguist jobs? States with the most job openings for Machine Learning Data Linguist jobs include:
What job categories do people searching Machine Learning Data Linguist jobs look for? The top searched job categories for Machine Learning Data Linguist jobs are:
Machine Learning Data Linguist jobs near you
Infographic showing various Machine Learning Data Linguist job openings in the United States as of July 2026, with employment types broken down into 56% Full Time, 33% Contract, and 11% Nights. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $73,373 per year, or $35.3 per hour.
Senior Machine Learning Data Scientist

Senior Machine Learning Data Scientist

Extend

Remote

$135K - $165K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted just now

Job description

About Extend:
Extend is revolutionizing the post-purchase experience for retailers and their customers by providing merchants with AI-driven solutions that enhance customer satisfaction and drive revenue growth. Our comprehensive platform offers automated customer service handling, seamless returns/exchange management, end-to-end automated fulfillment, and product protection and shipping protection alongside Extend's best-in-class fraud detection. By integrating leading-edge technology with exceptional customer service, Extend empowers businesses to build trust and loyalty among consumers while reducing costs and increasing profits.
Today, Extend works with more than 1,000 leading merchant partners across industries, including fashion/apparel, cosmetics, furniture, jewelry, consumer electronics, auto parts, sports and fitness, and much more. Extend is backed by some of the most prominent technology investors in the industry, and our headquarters is in downtown San Francisco.
About the Role:
The Fraud & Machine Learning team is the secret sauce behind Extend's post-purchase protection platform. As a Senior ML Data Scientist, you will own the development of cutting-edge machine learning models based on signals and transactions from hundreds of millions of users to detect and prevent fraud, assess risk, and unlock business value.
You will drive the full data science lifecycle - from requirements and feature engineering through model development, evaluation, and monitoring. You'll partner closely with Product, Engineering, and our Fraud Intelligence team to translate messy data into scalable, production-grade ML systems that stop bad actors in their tracks. If you're impact-driven and excited to tackle complex problems at the intersection of core machine learning and fraud prevention, you'll thrive on our team!
What You'll Be Doing:
  • Own the model lifecycle: requirements, experimentation, model development, evaluation, and model cards, partnering with ML engineers on deployment and production infrastructure
  • Translate complex fraud patterns into well-framed ML solutions: defining what to model, what success looks like, and where ML adds value vs. simpler approaches
  • Design and maintain feature engineering pipelines for model development
  • Monitor model quality in production, tracking performance over time, detecting data drift, and determining when to retrain
  • Partner closely with leadership, go-to-market, fraud operations, product, and engineering teams to define and execute effective fraud strategies
  • Champion a culture of continuous learning, experimentation, and collaboration across the fraud and broader data science teams

What We're Looking For:
Required:
  • Hands-on, proactive, and analytical professionals who are passionate about using data to solve complex, real-world problems
  • Bachelor's degree or higher in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Operations Research, Physics or related field
  • 3+ years of work experience building and deploying machine learning systems into production
  • Strong proficiency in Python and SQL
  • Strong understanding of ML fundamentals: model selection, evaluation methodology, feature engineering, and common failure modes
  • Hands-on experience with PyTorch, scikit-learn, and XGBoost (or similar gradient boosting frameworks)
  • High attention to detail, strong intellectual curiosity, and a deep understanding of user behavior and fraud patterns
  • Empathetic, humble, and collaborative team player
  • Candidates must be located within the continental United States

Preferred:
  • Experience building fraud detection or risk assessment systems
  • Experience with cloud ML platforms, particularly AWS (e.g., SageMaker)
  • Experience with graph data and graph-based models (e.g., PyTorch Geometric)
  • Experience with model monitoring and observability tooling (e.g., Arize)

Estimated Pay Range: $135,000 - $165,000 per year salaried*
* The target base salary range for this position is listed above. Individual salaries are determined based on a number of factors including, but not limited to, job-related knowledge, skills and experience.
Life at Extend:
  • Working with a great team from diverse backgrounds in a collaborative and supportive environment.
  • Competitive salary based on experience, with full medical and dental & vision benefits.
  • Stock in an early-stage startup growing quickly.
  • Generous, flexible paid time off policy.
  • 401(k) with Financial Guidance from Morgan Stanley.

Extend CCPA HR Notice

Apply