Manager, Software Engineering, Linguistics

Facebook

Redmond, WA, USA

Full-time

Oct 25

This job is no longer accepting applications.

The Facebook Reality Labs AR/VR team at Facebook is helping more people around the world come together and connect through world-class Augmented, Mixed, and Virtual Reality hardware and software. With global departments dedicated to AR/VR research, machine perception, graphics, operating systems, social interaction, and more, we are committed to driving the state-of-the-art forward through relentless innovation. AR and VR’s potential to change the world is immense.


As a Linguistic Engineering (LE) Manager, 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, Reasoning, and the Knowledge Graph. The LE Manager plays a role in managing the complex data and language requirements from the cross-functional teams that work on these components, and translating those into LE workstreams. The LE Manager helps the team deliver 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 desired for this role. The ideal candidate will 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.Manager, Software Engineering, Linguistics Responsibilities

  • Guide the team in building datasets, pipelines, and models for ML applications
  • Support a team of Linguistics Engineers, many with backgrounds spanning data skills and computational linguistics, and help the team develop their technical skills further
  • Clearly communicate with project stakeholders
  • Identify best practices and improve procedures across data systems
  • Drive projects from conceptualization through launch and beyond with continual improvement and support
  • Design and conduct product experiments
  • Work in a dynamic, ambiguous work environment
  • Be self-driven and prioritize multiple work streams without oversight
  • Collaborate seamlessly with cross-functional teams

Minimum Qualifications

  • 5+ years of work experience as data scientist, software engineer, computational linguist or in similar role
  • 2+ years of experience directly managing a team of data scientists, software engineers, or computational linguists or similar
  • Experience with programming and data analysis with languages and platforms such as Python, SQL, PHP/Hack
  • Experience with text analysis, scripting, relational database, No SQL databases or similar
  • Experience recruiting and managing technical teams, including performance management
  • Demonstrated experience collaborating with other internal and external teams
  • Experience shipping multiple products across various platforms

Preferred Qualifications

  • 7+ years of work experience as data scientist/software engineer/computational linguist, with experience in machine learning and knowledge graph integrations with lexicons or ontologies
  • 5+ years of experience directly managing a technical team
  • 5+ years relevant industry experience managing technical teams as part of a consumer-facing application
  • Deep understanding of the relationship between data and machine learning models
  • Experience with larger scripting projects that involve combining language data from different sources, computing complex metrics over large datasets, etc.
  • Experience designing and conducting data experiments
  • Familiarity with version control, unit tests, and other programming best practices
  • Fluency in additional spoken languages
  • Advanced coursework and/or research in Computer Science, Data Science, Computational Linguistics, Information Systems, or related fields


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