WHO WE ARE:
We are a producers playground, delivering music creators the tools they need to bring their ideas to life. With a massive, industry-leading catalog of licensed samples, paired with powerful AI, and access to affordable plugins and DAWs, Splice kicks sound discovery, inspiration, and creative output into overdrive.
HOW WE WORK:
At Splice, DISCO is a rallying cry for collaboration, accountability and unity within our organization; Direct, Inclusive, Splice Together, Creator Centric and Optimistic. Our shared success depends on our ability to support one another, work well together and communicate directly. By embracing flexibility and a unified approach, we can navigate anything that’s thrown at us.
Splice embraces a culture of remote work. You’ll see your colleagues showing up from across the US and the UK. In order to keep us working well as a team, we have regular communication, including Town Halls, departmental All Hands and get-togethers.
When you join Splice, you join a network of colleagues, peers, and collaborators. Are you ready?
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 and prior art research in the field of ML-based generative audio. Explore novel approaches for high-fidelity, performant audio generation, including latent diffusion, Transformed-based decoder architectures, neural audio codecs, as well as specific model building blocks such as VQ-VAE and CLAP.
- 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 or Transformer-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.
Splice is an Equal Opportunity EmployerSplice provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
