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Meta · 9 hours ago

Software Engineer, Audio Applied Scientist

Burlingame, CA

Full-time

Onsite

Senior Level

7+ years exp

Meta is a company focused on building technologies that enhance human connection and community. They are seeking an Audio Applied Scientist to develop innovative audio technologies and create immersive audio experiences that redefine how people interact with sound in virtual and augmented environments.

Computer Software

Comp. & Benefits

Responsibilities

Develop and implement innovative audio technologies, including general audio processing, audio ML/AI algorithms, and audio codecs

Identify areas for improvement in scalability, performance, quality, and reliability across the audio stack

Collaborate with cross-functional teams to deploy new audio technologies as-a-service and as-a-platform

Analyze, design, develop, and debug audio features on Android systems

Work effectively in a team environment, making architectural tradeoffs to deliver software solutions rapidly

Develop software for consumer devices, prioritizing efficiency and delivering high-quality results

Create clean, readable code and debug complex problems

Embrace continuous learning, adapt to new technologies, and navigate ambiguity in problem-solving

Qualification

Audio software engineeringCC++ programmingAudio signal processingMachine learning techniquesAndroid audio stackCross-functional collaborationTeamworkContinuous learning

Required

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

7+ years software development experience in industry settings or PhD with 4+ years of experience

3+ years relevant audio software engineering experience in industry settings

C or C++ experience, including use of C++11/14/17 features

Demonstrated experience working across disciplines to drive optimal solutions

Preferred

MS or PhD in Electrical Engineering, Computer Science or equivalent

Expertise in audio signal processing and auditory perception, both classical and machine learned techniques

Proven track record of innovation as demonstrated by products shipped, publications and/or patents

Proven track record of contribution in two or more of these areas: Design and deployment of ML models on resource constrained devices, near- and far-field spatial processing, Adaptive System Identification, multirate systems and filter banks, speech and audio compression, room acoustics or spatial audio

Experience with audio software development including DSP, machine learning, and/or hybrid systems

Experience in Android or Linux audio stack development

Experience developing, debugging, and shipping software products on large code bases that span platforms and tools

Demonstrated experience working collaboratively in cross-functional teams

Experience with audio-related software features across all layers of the audio stack