The Creative Audio team is seeking a Creative Coder for the Tech & Prototypes department. This role collaborates closely with Engineering and Product Design to define sound functionality and deliver advanced audio systems. It involves developing advanced audio solutions, optimizing performance, refining tools, and solving complex technical challenges. As a key contributor and leader to Meta’s day-to-day sound design, the Creative Coder provides creative and technical insights to drive immersive and agentic audio experiences, offering a long runway for creativity, innovation, and empowerment to push the boundaries of sound technology and make a meaningful impact.
Responsibilities
Identity potential large scale opportunities within Meta and partner with design and engineering teams to deliver state of the art audio functionality, tooling and pipeline solutions Provide audio engineering leadership to cross-functional partners, improving audio quality and automating workflows across Meta products and platforms through agentic pipelines Use creativity and product thinking to develop audio-focused prototypes and experiences that drive team and company success Support AI Audio teams throughout every stage of the model lifecycle, from training through implementation Implement existing audio models into product pipelines Build functional prototypes from early concepts across a range of prototype fidelities, using a variety of design tools and programming languages, and implement on multiple platforms Drive audio specific features from a technical perspective, ensuring scalability and high performance quality Convey prototype design decisions to internal stakeholders and provide feedback to partners Prep and test for implementation accuracy as well as collaborating with internal and external team members to address bugs and optimize sounds in the product Leverage code as a design medium to bridge the gap between product goals and engineering implementation, as well as unlock features for external developers Demonstrate thought leadership in the convergence of artificial intelligence and audio technologies, actively staying informed on state-of-the-art developments and industry trends
Qualifications
7+ years implementing/coding sonic experiences for products in mobile, hardware, and/or non-traditional immersive environments 5+ years development experience with at least two of these languages: C++. Kotlin, Javascript, RUST and Python Experience building large scale audio programs with solid OOP architecture Demonstrated understanding of DSP and audio signal processing Experience implementing LLMs and Agentic behavior on AI audio workflows Experience debugging code in a variety of development environments Experience with managing collaboration tools and version control systems such as GitHub, Perforce, etc Experience leading projects and prioritizing, based on company goals Time-management and organizational skills to meet delivery specifications and deadlines BA/BS in Audio or Music Technology, Computer Science, Transmedia, or equivalent work experience Experience building AI audio pipelines using tools such as TensorFlow, PyTorch, Langchain and audio processing libraries (e.g., Librosa, torchaudio), integrating models, data preprocessing, feature extraction and building RAG pipelines An understanding of spatial audio, and experience implementing immersive sound experiences Experience with generative sound or music, speech synthesis, or NLP Audio Implementation and/or design for shipping AR and VR experiences (Unity, Unreal and/or Spark, React, Snap, MARS) Experience with WebAudio and/or Tone.js and/or OpenAL Experience with embedded software development for audio consumer electronics hardware Knowledge of acoustics, equipment set ups and calibration experience with hardware and electronic prototypes and configuration Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) 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