招聘
必备技能
PyTorch
Machine Learning
Job Posting Title:
Sr Staff R&D Engineer:
Req ID:
10127968
Job Description:
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.
This role is considered Hybrid, which means the employee will work onsite in our Nicasio, CA office and occasionally from home.
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.
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Drive the architecture and deployment of scalable model training pipelines using Py Torch 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.
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Own end-to-end model lifecycle management: pretraining, fine-tuning, validation, inference optimization, and CI/CD integration.
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Guide the development of personalized model adaptation workflows to support per-user tuning, cross-project continuity, and flexible deployment.
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Collaborate with product, platform, and engineering leads to define integration strategies within a secure, cloud-optimized SaaS environment.
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Stay at the forefront of generative audio, multi-modal modeling, and self-supervised learning—translating emerging research into applied innovation.
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Contribute to internal tooling and infrastructure that improves iteration speed, reproducibility, and explainability of deployed models.
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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.
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5 years of professional experience in applied ML, with a deep focus on audio-centric AI/ML research and deployment.
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Expertise in building and scaling models using Py Torch, with fluency in training, fine-tuning, and inference for deep neural networks.
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Demonstrated experience developing generative models such as VAE, GAN, diffusion models, or neural vocoders (e.g., Hi Fi-GAN, Wave Net).
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Deep understanding of audio-specific ML domains, including source separation, speech enhancement, music processing, and cross-modal tasks.
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Experience with MLOps tooling (e.g., Weights & Biases, MLflow, Datachain), Docker-based containerization, and scalable infrastructure for distributed training.
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Fluency in audio signal processing fundamentals and the integration of DSP into ML pipelines.
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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.
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Experience implementing real-time or near-real-time inference pipelines in cloud or edge environments (e.g., AWS, GCP, on-prem GPUs).
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Working knowledge of latent diffusion audio models (e.g., stable-audio, AudioLDM, Audio Gen).
-
Strong knowledge of industry-standard audio datasets and benchmarks (Libri Speech, VCTK, MUSDB, etc.).
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Experience optimizing inference pipelines for creative applications or interactive use.
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Proficiency in lower-level audio frameworks (C / C++, etc.)
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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.
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
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关于ESPN (Disney)

ESPN (Disney)
PublicThe happiest place on earth.
1,001-5,000
员工数
Bristol
总部位置
评价
3.7
10条评价
工作生活平衡
2.8
薪酬
4.0
企业文化
3.8
职业发展
2.5
管理层
2.5
65%
推荐给朋友
优点
Great benefits and competitive compensation
Supportive team and team spirit
Innovative and interesting projects
缺点
Long hours and overwhelming workload
Work-life balance issues
High expectations and tight deadlines
薪资范围
435个数据点
Junior/L3
Mid/L4
Junior/L3 · Content Associate
78份报告
$54,118
年薪总额
基本工资
$50,664
股票
-
奖金
$3,454
$37,430
$78,777
面试经验
1次面试
难度
3.0
/ 5
时长
14-28周
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
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