Research Scientist

Location
: 9845 Willows Road NE, Redmond, WA

Contract
: 12 Months

Pay Rate
: $86.10,hr, W2

Benefits
:
Medical, Dental, Vision and Weekly Pay

Reality Labs Research is a leading research organization of world-class researchers, developers, and engineers, who collaborate to actively create a future where virtual and augmented reality become as indispensable as today s smartphones and personal computers.

The mission of the Reality Labs Research Audio team is to engineer augmented audio that redefines human hearing capabilities. This will allow us to connect people by facilitating conversation in even the most challenging auditory environment.

We are seeking a contract applied research scientist specializing in building machine learning (ML) models that emulate auditory perception. This role is an integral part of our team, contributing to our research and development efforts. The ideal candidate will help us explore and understand individualized audio quality preferences and experiences, enabling us to tailor our technologies to meet unique user needs.

• Drive research on improved machine learning models for speech quality, run computational experiments and report findings.
• Implement ML models that emulate aspects of human auditory perception.
• Independently implement ML training pipelines, models, and evaluation frameworks.
• Regularly report on project progress, dependencies and risks to stakeholders.
• Support research scientists and engineers within the team.
• Execute on applied coding tasks in support of the team s goals.
• Interpersonal and communication skills, with strong attention to detail.
• Proactive with ability to execute on multiple projects simultaneously.
• Strong organizational and time management skills.
• Track record of communicating research on ML perception in an academic or industrial setting.
• Experience working in a fast-paced research and/or product development environment.
• Experience with Python or other scientific programming languages.
• Previous experience designing, training, and evaluating neural networks in Pytorch.
• Experience working in a high performance computing environment.
• Master s degree or equivalent experience in Computational Neuroscience, Cognitive Science, Electrical Engineering, Perception, Experimental Psychology, Audio Engineering, Acoustics, Computer Science, Computer Engineering, Biomedical Engineering, Computational Audiology or a related field.

• Deep Learning for Audio/Speech Processing
  :
  The role requires building ML models for speech quality assessment and auditory perception. The candidate must have hands-on experience designing, training, and evaluating neural networks specifically for audio applications using PyTorch (Tensor Flow, Keras much less desirable).
• Psychoacoustic & Perceptual Modeling Expertise
  :
  The candidate must understand how humans perceive audio quality, including concepts like speech intelligibility, listening effort, speech degradation, and noise noticeability. This is critical for building models that accurately predict subjective Mean Opinion Scores (MOS) and enable features like Conversation Focus to be evaluated computationally rather than through time-consuming user studies.
• ML Training Pipeline & Evaluation Framework Development
  :
  The role requires independently implementing end-to-end ML pipelines: data preparation, model training, hyperparameter tuning, and evaluation using metrics like MAE, Pearson correlation, SI-SDR, PESQ, STOI. Experience with HPC environments for large-scale training is essential.

• Binaural audio processing and spatial audio quality assessment
• Experience with audio-visual ML models (multi-modal learning)
• Familiarity with hearing science metrics (HASQI, HASPI, PESQ, POLQA)
• Signal processing fundamentals (DSP, beamforming, acoustic measurements)
• Experience with human participant research and perceptual data collection
• Background in computational hearing science or auditory cognitive neuroscience

Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position.

These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation.