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Salary
≈ $225k – $418k per year (Estimated)
Location
In office (Sunnyvale)
Seniority
Senior · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 2, 2026. First seen by Alion on Aug 4, 2026. Meta scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Meta Platforms is an American technology company founded in 2004 as Facebook and renamed in 2021 to signal its investment in immersive computing. It operates the largest family of social and messaging applications in the world, comprising Facebook, Instagram, WhatsApp, Messenger and Threads, and earns almost all of its revenue from advertising sold against that audience. Headquartered in Menlo Park, California, the company also develops the open Llama language models and the Reality Labs division behind Quest headsets and Ray-Ban smart glasses.
We are the teams who create all of Meta's products used by billions of people around the world. Want to build new features and improve existing products like Messenger, Video, Groups, News Feed, Search, AR/VR, GenAI and more? Want to solve unique, large scale, highly complex technical problems? Meta is seeking experienced Audio Applied Scientists to join our teams. You can help build the technologies that help us connect the next billion people, create new features that have billions of interactions per day and be a part of a team that’s working to help people connect with each other around the globe.

As an Audio Applied Scientist at Meta, you can help build new, innovative technologies and software that improve the way people work, play, and connect and especially how they hear the virtual and augmented world or interact with GenAI bots. What we build today could one day be the norm. So to be here today is to be part of a team shaping new products and technologies. We may not have all the answers. But together, we're getting closer.

Responsibilities

Research, design, and develop advanced signal processing algorithms with application to speech and audio Define and build new algorithms and add enhancements to existing algorithms to support human listening, machine listening, and other new experiences for communications Build specialized Machine Learning (ML) for resource constrained platforms (e.g., mobile/wearables). Explore new paradigms in AI and Machine Learning Hands-on implementation and optimization of algorithms for classical DSP and ML inference engines Contribute to roadmap planning for the next generation of platforms Collaborate with other researchers/scientists, engineers, cross-functional partners from multiple disciplines

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Solid understanding in fundamentals of Digital Signal Processing (DSP) and Machine Learning (ML) 5+ years of software development experience in audio, signal processing, or related technical domains 3+ years relevant audio software engineering experience including DSP/ML audio algorithm development in industry settings Demonstrated communication skills and experience working across disciplines to drive optimal solutions and supporting cross functional teams Experience with C or C++ and with scientific programming languages such as MATLAB, Python or similar Experience in any of the following areas: Small footprint ML, Differential DSP, Echo/Noise reduction, Spatial Processing, Hearing Aids Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies MS or PhD in Electrical Engineering, Computer Science or equivalent Proven track record of innovation as demonstrated by products shipped, publications and/or patents Expertise in audio signal processing both classical and machine learning techniques Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience developing GenAI systems Experience communicating technical concepts to peers, partners, and non-technical stakeholders through written and verbal channels (e.g., design docs, presentations, cross-functional reviews)

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