United States
Redwood Materials
The Walt Disney Company
Sr Staff R&D Engineer - Skywalker Sound
RemoteUnited States
Nicasio, California, United States
AWSGCPDockerC++
About the opportunity
Job Posting Title:
Req ID: 10127968
This role is considered Hybrid, which means the employee will work onsite in our Nicasio, CA office and occasionally from home.
Job Posting Segment: Skywalker Sound
Job Posting Primary Business: Skywalker Sound-Engineering
Primary Job Posting Category: Software Engineer
Employment Type: Full time
Primary City, State, Region, Postal Code: Nicasio, CA, USA
Alternate City, State, Region, Postal Code:
Date Posted: 2025-08-19
Job Description
Sr Staff R&D Engineer - Skywalker Sound
The Skywalker Sound Development Group is seeking a highly accomplished Sr Staff R&D Engineer (AI/ML) to lead the development of transformative audio intelligence technologies for global media production. This senior-level role is central to advancing our next-generation soundtrack platform, with a focus on speech processing, style transfer, upmixing, source separation, and generative audio synthesis.
You will architect, build, and optimize cutting-edge machine learning systems at scale—leveraging foundational models, neural vocoders, latent diffusion models, and advanced retraining workflows. As a core member of our applied R&D team, you will contribute to technical direction, collaborate across product and engineering, and deliver production-ready solutions that integrate seamlessly into creative and operational workflows for elite content creators worldwide.
What You’ll Do *
- Lead the research, design, and implementation of state-of-the-art machine learning algorithms for speech processing, voice transfer, source separation, and upmixing in media post-production environments. *
- Drive the architecture and deployment of scalable model training pipelines using PyTorch and distributed computing frameworks. *
- Develop novel generative audio models, including latent diffusion, flow-based models, variational autoencoders, and neural vocoders, optimized for professional soundtrack production. *
- Own end-to-end model lifecycle management: pretraining, fine-tuning, validation, inference optimization, and CI/CD integration. *
- Guide the development of personalized model adaptation workflows to support per-user tuning, cross-project continuity, and flexible deployment. *
- Collaborate with product, platform, and engineering leads to define integration strategies within a secure, cloud-optimized SaaS environment. *
- Stay at the forefront of generative audio, multi-modal modeling, and self-supervised learning—translating emerging research into applied innovation. *
- Contribute to internal tooling and infrastructure that improves iteration speed, reproducibility, and explainability of deployed models. *
- Mentor junior researchers and engineers, and contribute to a culture of rigorous experimentation, collaboration, and continuous improvement.
Minimum requirements
What We’re Looking For *
- MSc or PhD in Computer Science, Electrical Engineering, Applied Math, or a related field with a focus on AI/ML and mult-imodal signal processing. *
- 5 years of professional experience in applied ML, with a deep focus on audio-centric AI/ML research and deployment. *
- Expertise in building and scaling models using PyTorch, with fluency in training, fine-tuning, and inference for deep neural networks. *
- Demonstrated experience developing generative models such as VAE, GAN, diffusion models, or neural vocoders (e.g., HiFi-GAN, WaveNet). *
- Deep understanding of audio-specific ML domains, including source separation, speech enhancement, music processing, and cross-modal tasks. *
- Experience with MLOps tooling (e.g., Weights & Biases, MLflow, Datachain), Docker-based containerization, and scalable infrastructure for distributed training. *
- Fluency in audio signal processing fundamentals and the integration of DSP into ML pipelines. *
- Proven ability to contribute to architectural planning, research strategy, and production deployment in complex, multi-stakeholder environments.
Preferred Qualifications *
- Familiarity with audio/text/video multi-modal frameworks and cross-domain representations. *
- Experience implementing real-time or near-real-time inference pipelines in cloud or edge environments (e.g., AWS, GCP, on-prem GPUs). *
- Working knowledge of latent diffusion audio models (e.g., stable-audio, AudioLDM, AudioGen). *
- Strong knowledge of industry-standard audio datasets and benchmarks (LibriSpeech, VCTK, MUSDB, etc.). *
- Experience optimizing inference pipelines for creative applications or interactive use. *
- Proficiency in lower-level audio frameworks (C / C++, etc.) *
- Contributions to published research at top-tier conferences (NeurIPS, ICASSP, ICLR, Interspeech) and/or open-source ML frameworks.
The hiring range for this position in Nicasio, CA is $209,500.00 to $280,900.00 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
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