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Chinese Machine Translation Jobs (NOW HIRING)

At our core is a low-latency, high-accuracy speech translation model that connects conversations so ... Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese ...

At our core is a low-latency, high-accuracy speech translation model that connects conversations so ... Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese ...

At our core is a low-latency, high-accuracy speech translation model that connects conversations so ... Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese ...

At our core is a low-latency, high-accuracy speech translation model that connects conversations so ... Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese ...

At our core is a low-latency, high-accuracy speech translation model that connects conversations so ... Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese ...

At our core is a low-latency, high-accuracy speech translation model that connects conversations so ... Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese ...

At our core is a low-latency, high-accuracy speech translation model that connects conversations so ... Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese ...

At our core is a low-latency, high-accuracy speech translation model that connects conversations so ... Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese ...

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Chinese Machine Translation information

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How much do chinese machine translation jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for chinese machine translation in the United States is $23.12, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $22.60 per hour, depending on experience, location, and employer.

What is Chinese machine translation?

Chinese machine translation refers to the use of computer software or artificial intelligence to automatically translate text or speech between Chinese and other languages. It involves complex algorithms and language models that analyze and convert linguistic structures. This technology is widely used in applications such as online translators, localization services, and cross-cultural communication tools. Advances in neural machine translation have greatly improved the accuracy and fluency of Chinese translations, but challenges remain due to nuances, idiomatic expressions, and context.

What are some common challenges faced when working on Chinese machine translation projects?

One common challenge in Chinese machine translation is handling the nuances of context and meaning, as the language relies heavily on word order and characters that can have multiple meanings. Additionally, translating idiomatic expressions and cultural references accurately can be difficult, requiring close collaboration with native speakers and linguistic experts. Machine translation specialists often work in multidisciplinary teams, coordinating with software engineers and linguists to train and refine models, ensuring output quality meets industry standards. Regularly reviewing and updating datasets is also essential to keep up with language evolution and domain-specific terminology.

What are the key skills and qualifications needed to thrive as a Chinese machine translation specialist, and why are they important?

To thrive as a Chinese Machine Translation Specialist, you need strong bilingual proficiency in Chinese and English, a background in linguistics or computational linguistics, and experience with natural language processing concepts. Familiarity with CAT tools, machine translation engines like Google Translate or SDL Trados, and programming languages such as Python is typically required. Attention to detail, problem-solving ability, and effective cross-cultural communication are essential soft skills for this role. These skills ensure high-quality translation output, effective system customization, and the ability to bridge linguistic and technical gaps in multilingual projects.

What is the difference between Chinese Machine Translation vs Chinese Localization Specialist?

AspectChinese Machine TranslationChinese Localization Specialist
CredentialsLanguage processing skills, familiarity with translation toolsLanguage proficiency, cultural knowledge, translation experience
Work EnvironmentSoftware development, AI, NLP teamsMarketing, product development, content creation teams
Industry UsageAutomated translation, AI applicationsContent adaptation, cultural customization

Chinese Machine Translation focuses on developing and improving automated translation systems, primarily using AI and NLP technologies. In contrast, Chinese Localization Specialists adapt content to fit cultural and linguistic nuances for target audiences. While both roles require language skills, the former emphasizes technical and algorithmic expertise, whereas the latter centers on cultural understanding and content adaptation.

What other helpful pages are available for Chinese Machine Translation?

Other pages related to Chinese Machine Translation:

Infographic showing various Chinese Machine Translation job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 84% Full Time, 9% Part Time, 1% Temporary, 2% Contract, and 3% Nights. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $48,096 per year, or $23.1 per hour.

Artificial Intelligence Researcher

Santa Clara, CA • On-site

Kotoba
Translation Services • 1 - 10 employees

Other

Posted 20 days ago


Job description

Kotoba's speech models are licensed to Fortune 50 companies and US big tech, and power an app reaching 2,000–3,000 new users a day. We're hiring an AI Researcher to build the next generation of real-time, interactive voice AI.


Location: San Francisco. You'll work on full-duplex speech-to-speech, speech-to-text, and text-to-speech systems — models that don't just understand and generate high-quality speech, but hold the flow of a conversation: turn-taking, interruptions, overlapping speech, backchannels, response timing, prosody, and latency. Your work runs the full research lifecycle, from framing the question through distributed training, evaluation, and production deployment.


â–  About Kotoba

Kotoba is a generative AI company on a mission to become the default for voice AI in East Asia. At our core is a low-latency, high-accuracy speech translation model that connects conversations so naturally it feels as though both speakers share the same language, supporting Japanese, English, Korean, Chinese, Spanish, and other major language pairs. We also build ultra-low-latency speech-to-text and text-to-speech models that run everywhere from the data center to edge devices, and we license this foundational technology to Fortune 50 companies and major US tech firms. We work from two hubs: Tokyo and San Francisco.

Our own product, the Kotoba app, is available on iOS and Android. Since launch it has grown to a steady 2,000–3,000 new downloads per day and reached No. 1 in its App Store and Google Play category, ahead of the likes of Google Translate. Enterprise adoption is accelerating in Japan, and the app has supported nearly 100 live events including SusHi Tech Tokyo.

Kotoba was founded in 2023 by two Japanese generative AI researchers with PhDs from top US universities. We've raised over ¥3 billion (roughly US$23M) from prominent VCs in Japan and the US — including Kindred Ventures and Globis Capital Partners — and from the corporate venture arms of leading US and Japanese enterprises. We also receive strong government support in Japan for AI model training.


â–  What you'll do

  • Define and execute research projects for next-generation voice AI across speech-to-speech, speech-to-text, and text-to-speech systems
  • Develop full-duplex conversational models that listen and speak simultaneously while handling turn-taking, interruptions, overlapping speech, backchannels, and end-of-turn prediction
  • Improve the accuracy, naturalness, expressiveness, multilingual robustness, and streaming latency of speech recognition and speech generation models
  • Conduct multilingual and cross-lingual research, particularly for Japanese, Korean, Chinese, English, and other languages central to our products
  • Explore architectures that orchestrate speech, language, reasoning, retrieval, and tool-use models behind a unified real-time voice interface
  • Build and scale model training and inference pipelines on distributed GPU infrastructure, optimizing models for low-latency deployment
  • Work with research, product, and infrastructure engineers to move promising research into our applications, APIs, SDKs, and customer projects


â–  What we're looking for

Required

  • A PhD or equivalent research experience in machine learning, speech processing, natural language processing, multimodal AI, human-computer interaction, or a closely related field
  • A strong research track record, demonstrated through publications at leading conferences or journals in machine learning, speech, NLP, or related areas
  • Deep expertise in at least one relevant area: speech-to-speech modeling, speech translation, spoken dialogue systems, speech recognition, speech generation, multimodal foundation models, large language models, or AI model orchestration
  • Hands-on experience designing, implementing, training, and evaluating modern neural models in PyTorch or JAX
  • Strong knowledge of modern speech and language architectures, including transformers, streaming models, autoregressive and non-autoregressive models, and foundation-model training
  • The ability to formulate original research questions, design rigorous experiments, analyze results critically, and turn promising ideas into working systems
  • Familiarity with large-scale model training, inference, data pipelines, distributed computing, and GPU-based experimentation
  • Strong written and verbal communication, including professional proficiency in English


Preferred

  • Research experience in full-duplex speech-to-speech, speech recognition, or speech generation — particularly turn-taking, interruptions, backchannels, dialogue timing, or conversational fluency
  • Research experience involving Japanese, Korean, Chinese, or other East Asian languages, including multilingual or cross-lingual modeling
  • Knowledge of audio tokenization, neural audio codecs, streaming speech recognition, streaming speech generation, or low-latency speech architectures
  • Experience with distributed training and efficient inference for large speech, language, or multimodal models
  • Research experience with systems that orchestrate multiple models, agents, retrieval components, reasoning modules, or external tools
  • Previous experience at an industrial research lab, major AI organization, technology company, or research-driven startup, particularly transferring research into production
  • A record of open-source contributions


â–  Location

San Francisco