Senior Machine Learning Engineer - Generative Models (Remote)

$165,000 - $206,000/Yr

Splice Co - New York, NY

Full-time - Senior

Remote - New York, NY

Specialty Trade Contractors

About the position

The Senior Machine Learning Engineer at Splice will focus on designing, adapting, and optimizing advanced model architectures for generative audio and music applications. This role is integral to the Splice AI & Audio Science team, which is dedicated to leveraging artificial intelligence to empower music creators. The position emphasizes collaboration, innovation, and the application of cutting-edge deep learning techniques in a remote work environment.

Responsibilities

• Design, adapt and optimize cutting-edge model architectures for generative audio/music applications.
• Collaborate with other Applied Researchers and Machine Learning Engineers to design, train, fine-tune, and deploy scalable models to production.
• Explore and implement core building blocks in generative models, such as general Variational Autoencoders (VAEs), Neural Audio Codecs (RVQ / VAE), GANs, Diffusion Models, and Transformer-based architectures.
• Contribute to integrating machine learning models into Splice's products, delivering new and creative experiences for music creators.
• Design and run experiments to benchmark the accuracy, quality and performance of trained models.
• Stay current with the latest advancements in machine learning applied to generative models in the audio domain, incorporating and sharing relevant insights into the applied research process.
• Document experiments, best practices, and lessons learned to facilitate knowledge sharing and maintain reproducibility.
• Provide technical guidance and training to team members on model training, evaluation, deployment and optimization techniques.

Requirements

• Master's or PhD degree in Electrical Engineering, Computer Science or related Engineering discipline.
• Proven ability and track record designing, training, evaluating and deploying machine learning models in production environments, powering real applications.
• 2+ years of hands-on experience with generative models architectures in the audio, image or language domains, with specific experience in Latent Diffusion Models and Transformer-based architectures.
• Proficiency in Python, C/C++, or CUDA, and strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch).
• Hands-on experience with cloud services (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Comfortable with software development best practices and version control systems (e.g., Git).

Nice-to-haves

• Familiarity with audio signal processing, music information retrieval (MIR), or audio synthesis techniques.
• Background or knowledge in music production.

Benefits

• Remote work flexibility
• Collaborative work environment
• Access to a network of colleagues and peers
• Regular communication through Town Halls and departmental All Hands