Sr Staff R&D Engineer

Résumé du poste:

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.

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 $206,400 to $276,700 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.