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Applied Linguistics Remote Jobs (NOW HIRING)

Mercor

Spanish Audio Evaluator - Expert

San Francisco, CA · Remote

$50/hr

Remote Commitment: 10-20 hours/week Role Responsibilities * Transcribe and optimize audio and video ... Background in linguistics, humanities, social sciences, journalism, translation/localization, or ...

Mercor

Spanish Audio Evaluator - Expert

New York, NY · Remote

$50/hr

Remote Commitment: 10-20 hours/week Role Responsibilities * Transcribe and optimize audio and video ... Background in linguistics, humanities, social sciences, journalism, translation/localization, or ...

Mercor

Russian Audio Evaluator - Expert

New York, NY · On-site +1

$50/hr

Remote Commitment: 10-20 hours/week Role Responsibilities * Transcribe and optimize audio and video ... Background in linguistics, humanities, social sciences, journalism, translation/localization, or ...

Innodata Inc.

Applied AI Associate - Flexible Hours

$15/hr

It's a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact-on their schedule. Whether you're a writer, linguist, educator, researcher, or just ...

Innodata Inc.

Applied AI Analyst - Flexible Hours

$15/hr

It's a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact-on their schedule. Whether you're a writer, linguist, educator, researcher, or just ...

Tobii Dynavox

AAC Content Reviewer - Hungarian

Academic or applied background in Linguistics Project Commitment * Up to 50 hours over a 6-week ... Work is fully remote, with collaboration across time zones * Flexible scheduling within the agreed ...

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Applied Linguistics Remote information

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How much do applied linguistics remote jobs pay per year?

As of Aug 16, 2026, the average yearly pay for applied linguistics remote in the United States is $58,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,500.00 and $58,000.00 per year, depending on experience, location, and employer.

What is applied linguistics remote?

Applied linguistics remote jobs involve using linguistic theories and methods to solve real-world language-related problems, such as language teaching, translation, or language assessment, while working from a remote location. These roles can be found in education, research, technology, and publishing, and may include tasks like curriculum development, language data analysis, or developing language learning tools. Remote positions allow professionals to collaborate with teams and clients worldwide, making use of digital platforms to conduct their work efficiently.

What are the key skills and qualifications needed to thrive as an applied linguist in a remote role?

To excel as an Applied Linguist remotely, a strong background in linguistics, language analysis, and research—often supported by an advanced degree in applied linguistics or a related field—is essential. Familiarity with qualitative and quantitative research tools, linguistic software (such as ELAN or Praat), and data analysis systems is typically required. Outstanding written communication, self-motivation, and cross-cultural competency are important soft skills for effective collaboration and project management at a distance. These skills and qualities are crucial for producing impactful research, facilitating remote teamwork, and addressing diverse language-related challenges.

What are some common challenges faced by remote applied linguists, and how can they be addressed?

Remote applied linguists often encounter challenges such as coordinating with international teams across different time zones, maintaining effective communication in virtual environments, and staying updated with the latest research and software tools. To address these, it's helpful to establish clear routines for virtual meetings, utilize collaborative platforms for document sharing and feedback, and participate in online professional communities. Regularly scheduled check-ins and proactive communication can also foster a sense of team cohesion despite the physical distance.

What is the difference between Applied Linguistics Remote vs Language Analyst?

AspectApplied Linguistics RemoteLanguage Analyst
Required CredentialsMaster's degree in linguistics or related field, certificationsBachelor's or master's in linguistics, language proficiency tests
Work EnvironmentRemote, research, analysis, consultingRemote or on-site, intelligence agencies, government projects
Employer & Industry UsageUniversities, research institutes, private companiesGovernment agencies, defense, intelligence
Common Search & ComparisonApplied Linguistics RemoteLanguage Analyst

Applied Linguistics Remote and Language Analyst roles share a focus on language expertise, often requiring advanced degrees and language proficiency. While Applied Linguistics Remote emphasizes research, analysis, and consulting in various industries, Language Analysts typically work within government or intelligence sectors analyzing language data. Both roles can be remote, but their primary applications and employer types differ.

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Applied Linguistics Remote jobs near you
Infographic showing various Applied Linguistics Remote job openings in the United States as of August 2026, with employment types broken down into 40% Full Time, 30% Part Time, and 30% Contract. Highlights an 100% Remote job distribution, with an average salary of $58,415 per year, or $28.1 per hour.

Deep Learning Scientist, Speech Synthesis

Catapult Solutions Group

Saint Louis, MO • On-site, Remote

Contractor

Re-posted 23 days ago

Job description

08/06/26
The hiring manager is looking for people with experience working with autoregressive models, diffusion and flow matching models, FSQ and RVQ codec models, and full-duplex speech-to-speech models.
Deep Learning Scientist - Speech Synthesis
Update on 07/22/26:
No PHD is need just focus on seeking candidates with deep, hands-on expertise in Text-to-Speech (TTS), including experience developing and working with modern SOTA architectures and models. It is essential that their TTS background reflects work with the latest technologies and innovations in speech synthesis, demonstrating current industry knowledge and practical implementation experience.
Update as of 07/21/26: Hi,
We are specifically seeking candidates with deep, hands-on expertise in Text-to-Speech (TTS), including experience developing and working with modern SOTA architectures and models. It is essential that their TTS background reflects work with the latest technologies and innovations in speech synthesis, demonstrating current industry knowledge and practical implementation experience.
Thank you!
Location: 100% Remote (Anywhere in the U.S.)
Duration: 6-Month Contract
Position Overview
We are seeking a Deep Learning Scientist - Speech Synthesis to support the development of next-generation speech AI technologies. This role focuses on training and optimizing speech models, improving model performance, and solving complex machine learning challenges related to speech applications.
The ideal candidate has strong experience in speech synthesis (Text-to-Speech) or Speech-to-Text, deep learning, and Python development. Success in this role requires the ability to analyze model behavior, diagnose training issues, and improve model performance-not just collect or evaluate data.
Key Responsibilities
  • Train and optimize speech synthesis models, including mel spectrogram and vocoder models.
  • Analyze training metrics, validation losses, and model performance to identify root causes of model issues and recommend improvements.
  • Benchmark and optimize speech models across multiple use cases.
  • Improve speech data preparation, augmentation, filtering, and dataset quality.
  • Develop and refine high-quality training datasets for speech AI models.
  • Measure and characterize model accuracy, quality, and bias.
  • Collaborate with cross-functional teams to develop and deliver new speech AI features.
  • Participate in software development, design reviews, testing, and code reviews.
  • Troubleshoot technical issues and contribute to continuous model improvements.
Required Qualifications
  • Master's degree or Ph.D. in Computer Science, Electrical Engineering, Artificial Intelligence, Applied Mathematics, Linguistics, Computational Linguistics, or a related field (or equivalent experience).
  • 3+ years of relevant industry experience.
  • Strong Python programming skills.
  • Strong understanding of machine learning and deep learning concepts.
  • Experience with Text-to-Speech (TTS), Speech Synthesis, or Speech-to-Text (STT) technologies.
  • Hands-on experience training deep learning models using PyTorch.
  • Ability to analyze training behavior, validation losses, and model performance to troubleshoot and improve machine learning models.
  • Knowledge of speech signal processing concepts, including FFT, MFCC, and mel spectrograms.
  • Strong understanding of software development fundamentals.
  • Experience using version control systems such as Git, Gerrit, or GitLab.
  • Excellent communication and collaboration skills.
Preferred Qualifications
  • Experience with deep learning architectures such as CNNs, RNNs, LSTMs, and Transformers.
  • Experience with voice cloning or multilingual speech systems.
  • Knowledge of text normalization (TN), inverse text normalization (ITN), or grapheme-to-phoneme (G2P) systems.
  • Fluency in one or more languages such as Spanish, Mandarin, German, Japanese, Russian, French, Arabic, Hindi, Korean, Italian, or Portuguese.
  • Interest in linguistics, phonetics, and speech technologies.
  • Strong C++ programming skills.
  • Familiarity with GPU technologies such as CUDA, cuDNN, or TensorRT.
  • Experience deploying machine learning models to cloud, data center, or embedded environments.
What We're Looking For
The ideal candidate is someone who enjoys solving difficult machine learning problems and has hands-on experience training speech models. Beyond building models, we're looking for someone who can investigate why a model is underperforming, analyze validation losses, identify root causes, and improve overall model quality and performance.
Additional Information
  • 100% remote position within the United States.
  • No specific U.S. time zone requirement.
  • This is a contract opportunity.
  • Opportunity to contribute to cutting-edge speech AI and deep learning technologies.

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