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Machine Learning Data Linguist Jobs in California

Apple Inc.

Machine Learning - Data Scientist

Sunnyvale, CA · On-site

$150.40 - $277.60/hr

The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will ...

Welocalize, Inc.

Data Labeling Associate

San Diego, CA

$17 - $22/hr

MAIN TASKS & RESPONSIBILITIES Machine Learning Model Updates: * Update training and test model ... Ensure linguistic accuracy in all processed and annotated data. REQUIREMENTS Preferred ...

Welocalize, Inc.

Data Labeling Associate

San Diego, CA · On-site

$17 - $22/hr

MAIN TASKS & RESPONSIBILITIES Machine Learning Model Updates: * Update training and test model ... Ensure linguistic accuracy in all processed and annotated data. REQUIREMENTS Preferred ...

Apple

Machine Learning - Data Scientist

Sunnyvale, CA

$150K - $277K/yr

The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will ...

Vizcom

Machine Learning Data Engineer

San Francisco, CA · On-site

$163 - $208/hr

... data. Your job will be to help turn that trail into a machine. A design session isn't a simple ... Generous annual Learning & Development allowance * Paid parental leave * Weekly catered lunch at ...

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 ...

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Machine Learning Data Linguist information

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.

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 are popular job titles related to Machine Learning Data Linguist jobs in California?

For Machine Learning Data Linguist jobs in California, the most frequently searched job titles are:

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:

What cities in California are hiring for Machine Learning Data Linguist jobs?

Cities in California with the most Machine Learning Data Linguist job openings:

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

Bodega Bay, CA

PROPRIUS
See more jobs at PROPRIUSexternal

Full-time

Re-posted 14 days ago

Job description

Machine Learning Engineer

Location: San Francisco, CA

Sponsorship: No

Relocation: No

Industry: Machine Learning

Our client is a digital invention agency focused on machine learning methodologies, enterprise mobile and web applications, eCommerce, augmented reality and IoT. They look to innovatively make this world a better place with each and every product, system, idea and app they release.

Job Summary

Our client is looking for a machine learning engineer to join our existing ML team in developing and refining a predictive application.

The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.

You must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. You must have a proven ability to drive business results with their data-based insights. You must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

As a ML Engineer, you will:

  • Work with stakeholders throughout the organization to identify opportunities for leveraging data to drive business solutions
  • Mine and analyze data from databases to drive optimization and improvement of product development, marketing techniques and business strategies
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques
  • Develop custom data models and algorithms to apply to data sets
  • Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes
  • Coordinate with different functional teams to implement models and monitor outcomes
  • Develop processes and tools to monitor and analyze model performance and data accuracy

For this role you will need:

  • Strong with Statistics and can code in either R, Python, Java and Scala
  • Experience with designing and building using micro-services architectural pattern, web APIs using dotnet core & C#
  • Experience and passion for simulations, optimization, neural networks, artificial intelligence (deep learning and machine learning)
  • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, GIT, SQL, etc.
  • Able to understand statistical solutions and execute similar activities
  • Experience in data wrangling and advanced analytic modeling
  • Strong communication and organizational skills and has the ability to deal with ambiguity while juggling multiple priorities and projects at the same time
  • Experience visualizing/presenting data for stakeholders using: Seaborn, Business Objects, D3, ggplot, etc.
  • Ability to investigate the feasibility and data requirements necessary to develop an ML solution for a given problem
  • Ability to design, build and test production ready ML-based products while interpreting and explaining the basis for predictions generated by ML models

The perfect candidate will have:

  • Knowledge and experience using one or more of the following, or similar, machine learning software frameworks: CAFFE, Torch 7, Keras and Tensorflow
  • Experience building production-ready NLP or information retrieval systems
  • Hands-on experience with NLP tools, libraries and corpora (e.g. NLTK, Stanford CoreNLP, Wikipedia corpus, etc.)

PROPRIUS is an AI Industry recruiting firm. We’re lucky enough to recruit the best candidates into the most exciting companies all over the United States. We deliver performance.
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