Senior Machine Learning Engineer

Summary

Join Splice, a creative platform for music makers, as a Senior Machine Learning Engineer! Work remotely or from our NY office, collaborating with our AI & Audio Science team to design, develop, and deploy cutting-edge generative audio models. You will leverage deep learning techniques, work with various architectures (VAEs, GANs, Diffusion Models, Transformers), and integrate models into Splice products. This role requires a Master's or PhD in a related field, proven experience with generative models, proficiency in Python/C++/CUDA, and familiarity with cloud services and containerization. Splice offers competitive compensation, unlimited PTO, comprehensive health benefits, 401k matching, generous parental leave, flexible work options, and professional development opportunities.

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. Specific experience with Latent Diffusion Models and Transformer-based architectures is a must
• Proficiency in Python, C/C++, or CUDA. 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)

Responsibilities

• Design, adapt and optimize cutting-edge model architectures for generative audio/music applications, leveraging state-of-the-art deep learning techniques for audio/music synthesis
• 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
• Performance Benchmarking and Evaluation: 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
• Documentation and Knowledge Sharing: 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

Preferred Qualifications

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

Benefits

• Compensation & Equity: Competitive pay with annual reviews and equity opportunities
• Time Off: Unlimited PTO to recharge and thrive
• Health & Wellness: Comprehensive medical, dental, and vision coverage for you and your dependents
• Retirement Savings: 401(k) plan with immediate vesting and company match
• Parental Support: 12 weeks of fully paid parental leave for non-birthing parents, and 18-20 weeks for birthing parents
• Flexible Work Options: Work remotely or connect at our office hubs and creative spaces worldwide
• Professional Growth: Annual learning budget, leadership programs, and team ambassador opportunities
• Community & Connection: Inclusive events, team meet-ups, and vibrant Employee Resource Groups