Research Engineer - Language Models for Audio

Meta Platforms - Redmond, WA

- Mid Level

Redmond, WA

Broadcasting and Content Providers

About the position

At Meta's Reality Labs Research, our goal is to make world-class consumer virtual, augmented, and mixed reality experiences. Come work alongside industry-leading scientists and engineers to create the technology that makes VR and AR pervasive and universal. Join the adventure of a lifetime as we make science fiction real and change the world. We are a world-class team of researchers and engineers creating the future of augmented and virtual reality, which together will become as universal and essential as smartphones and personal computers are today. And just as personal computers have done over the past 45 years, AR and VR will ultimately change everything about how we work, play, and connect. We are developing all the technologies needed to enable breakthrough Smart glasses, AR glasses and VR headsets, including optics and displays, computer vision, audio, graphics, brain-computer interfaces, haptic interaction, eye/hand/face/body tracking, perception science, and true telepresence. Some of those will advance much faster than others, but they all need to happen to enable AR and VR that are so compelling that they become an integral part of our lives. The Audio team within RL Research is looking for a Research Engineer with experience in speech and audio natural language processing, and large language models. You will be doing applied research and applied engineering in technologies that improve listener's hearing abilities using wearable computing, and alongside a team of dedicated research scientists, developers, and engineers. You will operate at the intersection of large-scale machine learning systems design and development, and speech, hearing/audio health and hearing impairment technologies. You'll also contribute to novel egocentric audio-visual learning, acoustics, computer vision, and signal processing algorithms with hardware and software co-design.

Responsibilities

• Conduct applied research and engineering in speech and audio natural language processing.
• Develop technologies to improve listener's hearing abilities using wearable computing.
• Collaborate with research scientists, developers, and engineers on various projects.
• Contribute to novel audio-visual learning, acoustics, computer vision, and signal processing algorithms.
• Engage in large-scale machine learning systems design and development.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
• Master's degree or equivalent experience in Computer Sciences, Computer Engineering, Artificial Intelligence, Machine Learning, Robotics, Computer Vision, Computational Neuroscience, Signal Processing, Speech and Language technologies, or a related field.
• 3+ years of experience working on applied machine learning and natural language processing/understanding.
• 2+ years of experience evaluating, fine-tuning, and benchmarking large language models (like GPT, LLamas, etc.).
• Research-oriented software engineering skills, including fluency with machine learning libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Pandas).
• Experience in building collaborative relationships that lead to impact.
• Experience with architectural and system engineering on large scale software applications.

Nice-to-haves

• PhD degree or equivalent experience in Computer Sciences, Computer Engineering, Artificial Intelligence, Machine Learning, Robotics, Computer Vision, Computational Neuroscience, Signal Processing, Speech and Language technologies, or a related field.
• 2+ years of experience in speech, hearing, and audio perception research & technology development.
• 4+ years of experience working on applied machine learning and natural language processing/understanding, specifically on novel language models design, training, evaluating, and benchmarking.
• Experience in datasets and language prompts design for fine-tuning large language models.
• Experience in system optimization and hyperparameter tuning for improving language prompts based Assistants or recommender systems.