Research Engineer - Machine Learning

Meta•Redmond, WA

1d•$59 - $181,000

About The Position

Reality Labs (RL) is Meta’s innovation engine for next-generation AR/VR, AI, and wearable technologies. Our Audio team pioneers research and development at the intersection of sound, machine learning, and human experience—enabling new ways for people to connect, communicate, and collaborate. We are seeking an experienced Research Engineer specializing in Machine Learning Infrastructure to join our Reality Labs Audio team. You will be a technical leader supporting research and product development for AI wearables as part of Meta’s Superhuman Communication & Connection initiative. Your work will focus on building and optimizing ML infrastructure, including data pipelines, model training, evaluation, and validation—leveraging both companywide platforms and developing custom developed project-specific tools. By joining our team, you will have the opportunity to work on breakthrough technologies that redefine how people connect and communicate, collaborate with world-class researchers and engineers in a fast-paced, mission-driven environment, and shape the future of AI wearables and superhuman audio experiences.

Requirements

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 or Master’s degree in Computer Science, Electrical Engineering, or related field
2+ years of experience in machine learning infrastructure, data engineering, or related roles
Demonstrated programming skills in Python with a focus on ML training
Experience with common ML training platforms (e.g., Pytorch, Tensorflow)
Proven track record in building scalable data pipelines and ML training/evaluation systems
Familiarity with cloud computing, distributed systems, and large-scale data management
Demonstrated problem-solving, communication, and collaboration skills

Nice To Haves

Experience with biosignal and audio data processing for wearable devices
Hands on experience optimizing models for on-device, hardware inference
Background in AR/VR, multimodal sensing, or human-computer interaction
Experience integrating experimental research code into production infrastructure
Knowledge of best practices for ML model validation, monitoring, and deployment

Responsibilities

Design, implement, and maintain software and hardware pipelines for biosignal and audio data collection, processing, and analysis
Collaborate closely with research scientists to translate experimental algorithms and prototypes into robust, scalable engineering solutions
Develop tools and infrastructure for data management, annotation, and visualization to accelerate research workflows
Work cross-functionally with hardware, software, ML, and UX teams to deliver end-to-end solutions
Mentor less experienced engineers and contribute to technical execution
Document engineering processes and best practices for knowledge sharing and reproducibility
Architect, implement, and maintain scalable data pipelines for biosignal and audio data ingestion, processing, and storage
Build and optimize infrastructure for large-scale model training, hyperparameter tuning, and distributed computing
Develop robust systems for model evaluation, validation, and deployment, ensuring reproducibility and reliability
Integrate companywide ML platforms with project specific tools to accelerate research and product workflows
Develop dashboards and visualization tools for monitoring data and model performance
Integrate biosignal and audio processing modules into wearable device platforms
Optimize system performance for real-time operation, reliability, and scalability
Support deployment of machine learning models for biosignal interpretation and audio enhancement