Research Engineer, Language - Wearables Voice AI

Meta; New York (NY); Vor Ort; USD 140.000 - 190.000; Vollzeit

Zusammenfassung

Meta Wearables Research is seeking a Research Engineer to advance the device-driven AI Assistant for Ray-Ban Smart Glasses and future wearables. You will build state-of-the-art LLMs, optimize for on-device and server use, and deliver personalized, knowledge-grounded AI via a voice interface.

Collaboration with GenAI and FAIR is emphasized. You will apply advanced ML techniques to speech/LLM tech, develop scalable models, and contribute to experiments from design to evaluation, driving results

Qualifikationen

• Bachelor's degree in CS, CE, or a related field, or equivalent practical experience.
• 2+ years of AI research and development with emphasis on speech and ML.
• Experience with speech recognition algorithms, training, and LLMs.
• Proficiency with PyTorch or TensorFlow and Python scripting.
• Ability to work cross-functionally and translate research to production.

Aufgaben

• Apply AI/ML techniques to build speech/LLM tech for Wearables products.
• Develop novel algorithms and scalable systems for large-scale applications.
• Design experiments, implement reusable code, run evaluations, and organize results.
• Work with large data and contribute to large-scale foundation models.
• Create methods, tools, and infrastructure to improve model performance.

Kenntnisse

Speech recognition

Speech synthesis

Natural language understanding

Machine learning

LLMs

Cross-functional collaboration

Research to production

On-device/off-server ML

Ausbildung

Bachelor's degree in Computer Science or related field

Tools

PyTorch

TensorFlow

Python

Shell scripting

Jobbeschreibung

About

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

Minimum 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