Applied ML Researcher - GenAI / Generative Audio
To see similar active jobs please follow this link: Remote Development jobs
JOB TITLE Title: Applied ML Researcher - Generative Audio / GenAI
LOCATION: Remote
THE ROLE:
We are seeking an exceptional Applied Researcher with expertise in ML-based generative audio and a solid understanding of diffusion models. As a critical member of our applied research team, you will lead the charge in the design and implementation of ML models delivering performant, high fidelity audio synthesis. At Splice, we believe that Generative AI has the potential to extend the sonic boundaries of our human-made, world class catalog, and bring powerful unlocks to our users’ creative process.
TEAM INFORMATION:
The Splice AI & Audio Science team is dedicated to pushing the boundaries of artificial intelligence applied to audio data, with the mission to empower music creators everywhere. Being musicians ourselves, we are deeply committed to the use of AI in a creator-centric, ethical and responsible way. Our team consists of passionate and creative individuals who thrive in a collaborative, innovative, and fast-paced environment.
WHAT YOU’LL DO:
Generative Audio Research: Conduct literature research and experimentation in the field of ML-based generative audio, with a specific focus on diffusion models. Explore novel approaches to generate realistic, high-fidelity audio.
Model development: Collaborate with our ML Engineers to design performant model architectures for efficient ML-based audio synthesis, as well as adapting and fine-tuning existing models.
Prototyping: Develop proof-of-concept prototypes to showcase and validate capabilities and use cases using generative audio models. Iterate and refine models based on quantitative/qualitative feedback and evaluation metrics.
Collaboration: engage with academic and open source communities to stay up to date with the latest developments in the space, collaborate in joint projects, and identify top talent for our AI & Audio Science team’s future hiring needs.
Documentation and Knowledge Sharing: Document research findings, methodologies, and best practices. Collaborate with team members to disseminate knowledge and insights.
JOB REQUIREMENTS:
Ph.D. or Master's degree in Electrical Engineering, Computer Science or related Engineering discipline.
Background or proven experience in Digital Signal Processing.
Proven experience (3+ years) in an Applied Research role focused on ML-based generative audio. Alternatively, solid experience with diffusion-based models in the image domain, would be considered.
Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
Familiarity with software development best practices and version control systems (e.g., Git).
Strong communication and collaboration skills, with the ability to work cross-functionally with stakeholders in Engineering, Product and Design.
NICE TO HAVES:
A relevant portfolio of research projects, publications, or open-source contributions related to generative audio.
Prior experience in machine learning model optimization.
Background or knowledge in music production.
The national pay range for this role is $165,000 - $206,000. Individual compensation will be commensurate with the candidate's experience.
About the job
Applied ML Researcher - GenAI / Generative Audio
To see similar active jobs please follow this link: Remote Development jobs
JOB TITLE Title: Applied ML Researcher - Generative Audio / GenAI
LOCATION: Remote
THE ROLE:
We are seeking an exceptional Applied Researcher with expertise in ML-based generative audio and a solid understanding of diffusion models. As a critical member of our applied research team, you will lead the charge in the design and implementation of ML models delivering performant, high fidelity audio synthesis. At Splice, we believe that Generative AI has the potential to extend the sonic boundaries of our human-made, world class catalog, and bring powerful unlocks to our users’ creative process.
TEAM INFORMATION:
The Splice AI & Audio Science team is dedicated to pushing the boundaries of artificial intelligence applied to audio data, with the mission to empower music creators everywhere. Being musicians ourselves, we are deeply committed to the use of AI in a creator-centric, ethical and responsible way. Our team consists of passionate and creative individuals who thrive in a collaborative, innovative, and fast-paced environment.
WHAT YOU’LL DO:
Generative Audio Research: Conduct literature research and experimentation in the field of ML-based generative audio, with a specific focus on diffusion models. Explore novel approaches to generate realistic, high-fidelity audio.
Model development: Collaborate with our ML Engineers to design performant model architectures for efficient ML-based audio synthesis, as well as adapting and fine-tuning existing models.
Prototyping: Develop proof-of-concept prototypes to showcase and validate capabilities and use cases using generative audio models. Iterate and refine models based on quantitative/qualitative feedback and evaluation metrics.
Collaboration: engage with academic and open source communities to stay up to date with the latest developments in the space, collaborate in joint projects, and identify top talent for our AI & Audio Science team’s future hiring needs.
Documentation and Knowledge Sharing: Document research findings, methodologies, and best practices. Collaborate with team members to disseminate knowledge and insights.
JOB REQUIREMENTS:
Ph.D. or Master's degree in Electrical Engineering, Computer Science or related Engineering discipline.
Background or proven experience in Digital Signal Processing.
Proven experience (3+ years) in an Applied Research role focused on ML-based generative audio. Alternatively, solid experience with diffusion-based models in the image domain, would be considered.
Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
Familiarity with software development best practices and version control systems (e.g., Git).
Strong communication and collaboration skills, with the ability to work cross-functionally with stakeholders in Engineering, Product and Design.
NICE TO HAVES:
A relevant portfolio of research projects, publications, or open-source contributions related to generative audio.
Prior experience in machine learning model optimization.
Background or knowledge in music production.
The national pay range for this role is $165,000 - $206,000. Individual compensation will be commensurate with the candidate's experience.