engineer

Meta's AR/VR division is developing future products in augmented reality and virtual reality. Our work in conversational AI, computer vision, advanced optics, eye tracking, machine learning & reasoning will enable and empower consumers and businesses in new ways. As a Linguistic Engineer (LE), you will focus on helping deliver datasets, models, and knowledge that power the ML systems across all components in the voice assistant product, such as ASR/TTS, NLU, NLG, Dialog, LLMs, and a Knowledge Graph. The Linguistic Engineer delivers datasets, consistent models and representations across languages and areas, as well as data infrastructure that powers the voice assistant product. The ideal candidate has strong technical, analytical, and collaboration skills with experience in building datasets for ML applications. Experience as an ML practitioner is useful but not required as the role focuses on the datasets and provides an opportunity to interface and work directly with ML teams as part of the greater voice assistant organization. Experience with data tools, pipelines, and analytics is needed for this role. The ideal candidate will by multi-lingual, and have an interest in NLP and/or conversational AI systems and being at the cutting edge of their development. A plus is experience in any subfield of computational linguistics, though that is not specifically a requirement for the role. Linguistic Engineer Responsibilities <ul><li>Build datasets, pipelines, and models for ML applications. </li><li>Directly support product development with rules, prompts, and data patches. </li><li>Evaluate the quality of models and product experiences and close the feedback loop. </li><li>Clearly communicate with project stakeholders. </li><li>Identify best practices and improve procedures across data systems. </li><li>Drive and deliver projects from conceptualization through launch and beyond with continual improvement and support. </li><li>Design and conduct product experiments. </li><li>Work in a dynamic, ambiguous work environment. </li><li>Be self-driven and prioritize multiple work streams. </li><li>Collaborate seamlessly with cross-functional teams. </li></ul>Minimum Qualifications <ul><li>2+ years of work experience as data scientist, software engineer, computational linguist or in similar role. </li><li>Experience with programming and data analysis with languages and platforms such as Python, SQL, PHP/Hack. </li><li>Experience with text analysis, scripting, relational database, No SQL databases or similar. </li><li>Experience shipping multiple products across various platforms. </li></ul>Preferred Qualifications <ul><li>5+ years of work experience as data scientist/software engineer/computational linguist, with experience in machine learning and knowledge graph integrations with lexicons or ontologies. </li><li>Deep understanding of the relationship between data and machine learning models. </li><li>Experience with larger scripting projects that involve combining language data from different sources, computing complex metrics over large datasets, etc. </li><li>Experience designing and conducting data experiments. </li><li>Experience with version control, unit tests, and other programming best practices. </li><li>Fluency in additional languages. </li><li>Advanced coursework and/or research in Computer Science, Data Science, Computational Linguistics, Information Systems, or related fields. </li></ul> Start preparing Learn about how to prepare for your interview with our interview guide, tips, and interactive experiences. Visit interview prep

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