Description:

The Senior Machine Learning Engineer will design, adapt, and optimize cutting-edge model architectures for generative audio/music applications, utilizing state-of-the-art deep learning techniques for audio/music synthesis.
This role involves collaboration with other Applied Researchers and Machine Learning Engineers to design, train, fine-tune, and deploy scalable models to production.
The engineer will explore and implement core building blocks in generative models, including general Variational Autoencoders (VAEs), Neural Audio Codecs (RVQ / VAE), GANs, Diffusion Models, and Transformer-based architectures.
Responsibilities include integrating machine learning models into Splice’s products to deliver new and creative experiences for music creators.
The position requires performance benchmarking and evaluation, designing and running experiments to benchmark the accuracy, quality, and performance of trained models.
Staying current with the latest advancements in machine learning applied to generative models in the audio domain is essential, along with incorporating and sharing relevant insights into the applied research process.
Documentation and knowledge sharing are key aspects of the role, including documenting experiments, best practices, and lessons learned to facilitate knowledge sharing and maintain reproducibility.
The engineer will also provide technical guidance and training to team members on model training, evaluation, deployment, and optimization techniques.

Requirements:

A Master's or PhD degree in Electrical Engineering, Computer Science, or a related Engineering discipline is required.
The candidate must have a proven ability and track record in designing, training, evaluating, and deploying machine learning models in production environments that power real applications.
A minimum of 2 years of hands-on experience with generative model architectures in the audio, image, or language domains is necessary, with specific experience in Latent Diffusion Models and Transformer-based architectures being a must.
Proficiency in programming languages such as Python, C/C++, or CUDA is required, along with strong proficiency in machine learning frameworks like TensorFlow and PyTorch.
Hands-on experience with cloud services (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) is essential.
The candidate should be comfortable with software development best practices and version control systems, such as Git.
Familiarity with audio signal processing, music information retrieval (MIR), or audio synthesis techniques is a strong plus.
A background or knowledge in music production is also considered beneficial.

The national pay range for this role is between $165,000 and $206,000, with individual compensation commensurate with the candidate's experience.
Splice is committed to providing equal employment opportunities to all employees and applicants, prohibiting discrimination and harassment of any type.
The company embraces a culture of remote work, allowing employees to collaborate from various locations across the U.S. and the UK.
Regular communication and team-building activities, such as Town Halls and departmental All Hands, are part of the work culture to ensure effective collaboration and unity within the organization.