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Machine Learning Data Linguist Jobs in California

Prolim Global

Facebook - Linguist III

Burlingame, CA · On-site

We are seeking candidates with strong linguistic data analysis and language technology experience ... Experience with machine learning frameworks, NLP Libraries and Tools 2-3 Years of experience ...

Rule14

Be Seen First

Data Scientist Machine Learning

Santa Monica, CA · On-site

$75K - $100K/yr

As a Data Scientist Machine Learning, you will work within a small data science team focusing on predictive modeling, natural language processing, computer vision, recommender systems, and OCR ...

PTR Global

Linguist III

Daly City, CA · On-site

$50 - $55/hr

Linguist III Location: 100% remote Duration: 04+ months Contract Pay rate: $50-$55/hour on W2 Job ... machine learning, NLP, or software engineers, or data scientists. * Experience contributing to ...

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Machine Learning Data Linguist information

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.
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What job categories do people searching Machine Learning Data Linguist jobs in California look for? The top searched job categories for Machine Learning Data Linguist jobs in California are:
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Machine Learning Data Linguist jobs near you
Infographic showing various Machine Learning Data Linguist job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Machine Learning & Data Scientist, OS Power & Performance, CoreOS

Apple

San Diego, CA • On-site

Full-time

Re-posted 29 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Great performance is critical to Apple's product experience. We are seeking a Machine Learning & Data Scientist to help with quantitative analysis of high dimensional data to draw insights that would impact hundreds of millions of users. If the idea of developing data products to improve Apple's software & hardware performance excites you, we encourage you to apply!
Description
We're looking for a proactive & impact-driven engineer with excellent machine learning, analytical, problem solving and communication skills. In this role, you will analyze high dimensional data to derive meaningful insights and be responsible for producing metrics, models, simulations, and tools for analysis & communication of insights from large datasets. To be successful, you must have a strong foundation in statistical analysis and the ability to apply it to solving business & product-development problems, as well as a strong software engineering background with the ability to write production level code. As a member of this team, you will have the opportunity to provide meaningful insights to teams and influence decisions across Apple on a broad range of products.
Minimum Qualifications
Strong Quantitative Foundation: Education in Computer Science, Electrical Engineering, or a related quantitative field. Strong mathematical foundations, software engineering, and broad knowledge of data analysis and practical machine learning are expected.
Data Engineering and Analytics: Skilled at scalably transforming raw data into actionable insights through practical problem formulation followed by building of ETL processes (e.g. Python & Spark) and data visualizations (e.g. Tableau)
Business Acumen and Problem-Solving: Ability to understand the broader business context, solve complex problems, and communicate findings effectively to stakeholders.
Adaptability and Collaboration: Comfortable with ambiguity, eager to learn, and capable of working effectively in a collaborative environment. Strong interpersonal skills and the ability to build relationships with diverse stakeholders are essential.
Preferred Qualifications
M.S. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Statistics, or a similar quantitative field, with strong statistical skills and intuition
Proficiency in distributed compute & storage technologies such as HDFS, S3, Iceberg, Spark, and Trino
Proficiency with designing ETL flows and automation/scheduling (e.g. Kubernetes and Airflow)
Working knowledge of Operating Systems
Experience driving cross-functional projects with diverse sets of stakeholders
Skilled at connecting data insights to the company's overall strategy and objectives.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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