Research Engineer - Redmond, WA

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 ...

Job description

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.

Research Engineer - Machine Learning 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

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 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

Preferred Qualifications:

• 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

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-

$58.65/hour to $181,000/year + bonus + equity + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.