**Company: Unbabel Job Description Summary: Unbabel is a San Francisco-based company that offers a language operations platform combining AI and human editors for efficient translations. They work with top brands to provide multilingual support. As a Linguistic Engineer, you will enhance translation processes using CAT tools, AI, and quality analysis. Responsibilities include quality analysis, linguistic engineering, and linguistic research. Qualifications include a relevant BSc or MA, experience in linguistic engineering, and excellent communication skills in English. The ideal candidate should have attention to detail, tech savviness, and the ability to work independently in a fast-paced environment. Job Description: The company’s language operations platform blends advanced artificial intelligence with human editors, for fast, efficient, high-quality translations that get smarter over time. Unbabel integrates seamlessly in any channel so that agents can deliver consistent multilingual support from within their existing workflows. Making it easy for enterprises to grow into new markets and build seamless customer experiences in every corner of the world. Based in San Francisco, California, Unbabel works with leading customer support and marketing teams at brands such as Facebook, Microsoft, Booking.com, and Under Armour to communicate effortlessly with customers around the world, no matter what language they speak. What’s the opportunity about? As a Linguistic Engineer in the Community R&D Team at Unbabel, you will ensure the excellence of our human and AI-assisted translation processes. Leveraging your expertise in CAT tools, human translation quality analysis, and AI technologies, you will enhance our translation workflows aiming to improve the translation quality delivered to our customers. Your work will directly impact the development and evaluation of: Development of modules to train our Communities; Framework and methodologies for translation quality evaluation; AI and LLM technologies integrated into CAT tools, contributing to our Linguistic AI for Community. Responsibilities Quality Analysis Responsibilities Enhance the quality of human translations through our own CAT tool by applying your understanding of CAT tools. Analyze current quality metrics (MQM, MQM-QE, accuracy) and recommend additional data points for better linguistic data evaluation. Use Python (e.g., Pandas) for text data pre-processing to support quality analysis and perform rigorous data analysis to improve accuracy and throughput of annotated data. Utilize SQL to query databases and extract relevant data for analysis. Collaborate with QA engineers to conduct tests for features that impact translation quality. Work with Product and Engineering to build and refine internal and external tools to improve translation quality. Collaborate with other Linguistic Engineers and Community Managers to address quality issues during the translation process. Develop and deliver training modules for the Community to ensure best practices and continuous improvement in translation quality and translation evaluation. Linguistic Engineering Responsibilities Create effective prompts with and without fine-tuning to optimize large language models (LLMs) for translation tasks. Integrate AI and LLM technologies into CAT tools to enhance translation accuracy and efficiency, ensuring AI effectively aids the translation process. Linguistic Research Responsibilities Research novel methodologies from both industry and academia to improve translation quality. Study linguistic characteristics of diverse locales to ensure accurate and culturally sensitive translations.
Company:Unbabel
Qualifications:Translation Knowledge and Skills Strong understanding of translation studies and theoretical frameworks for translation quality. Proficiency in various CAT tools (e.g., SDL Trados, MemoQ, MateCat). Familiarity with translation quality evaluation technologies and methodologies (MQM framework, automatic metrics) Knowledge of subject matter expert translation workflows. Experience with style guides, quality checks, and translation quality analysis tools Soft Skills Lead training sessions to foster a culture of continuous learning. Collaborate effectively across departments, ensuring clear communication. Demonstrate strong problem-solving abilities and adaptability in a dynamic environment. Maintain high standards of accuracy in all tasks. Qualifications and Skills Relevant BSc degree or MA in the areas of Linguistics, Computational Linguistics and/or Translation Studies. Previous experience in linguistic engineering, computational linguistics, and/or language-based data science experience. Interest in Translation Quality evaluation methodologies (metrics and quality standards). Excellent communication and presentation skills in English. Experience working cross-functionally to create cohesion. Analytical and situational approach with unity as a guiding principle. English fluency (CEFR C1 upwards); multilingual preferred. Extensive translation knowledge and tech savviness. Attention to detail and excellent organizational skills. Ability to convey strategic concepts to diverse audiences. Influencing skills for representation of needs within the function. Ability to work independently and adapt in a fast-paced environment.
Educational level:Bachelor’s Degree
“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.
Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.
Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.
