About this role
As a Research Engineer in Wearables Voice AI, you will have the opportunity to perform innovative research to advance the device-driven AI Assistant effort at Meta – e.g. RayBan Smart Glasses and future Wearable devices. You will build state-of-the-art LLMs to support on-device and on-server use cases, optimize for natural voice interaction, deliver knowledge-grounded, actionable, personalized AI through a unique voice user interface. You will collaborate closely with Meta GenAI and Fundamental AI Research (FAIR) orgs to produce high-performance research and results.
Responsibilities
Apply relevant AI and machine learning techniques to build speech/LLM technology that will improve Meta Wearables products and experiences
Develop novel, accurate AI algorithms and advanced systems for large scale applications
Directly contribute to experiments, including designing experimental details, developing reusable code, running evaluations, and organizing results
Work with large data, and contribute to development of large scale foundation models
Design methods, tools, and infrastructure to push forward the capabilities and performance in large language models
Qualifications
Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
2+ years of experience in AI research and development, with emphasis on speech recognition, speech synthesis, natural language understanding, machine learning, deep learning, or related fields
Experience with development and implementation of speech recognition algorithm/ systems and model training, including LLMs
Experience working with machine learning libraries like Pytorch, Tensorflow, etc
Familiar with scripting languages such as Python and shell scripts Experience with developing scalable machine learning models in at least one of the following areas: automatic speech recognition, speech synthesis, LLM, or relevant areas
Experience working and communicating cross functionally in a team environment
Experience solving complex problems and comparing alternative solutions, tradeoffs, and broad points of view to determine a path forward
Experience with large scale model training, implementing algorithms, and evaluating speech-based systems
Experience taking ideas from research to production