Splice
Senior Machine Learning Engineer for generative audio/music applications, collaborating on cutting-edge model architectures and integrating ML into products.
Binance
Join Binance's blockchain development team as a Senior Solidity Engineer and collaborate on smart contract design & deployment.
Consensys
Mobile developer for Consensys, supporting Android & iOS platform development, collaboration with design & QA teams, and advancing web3 technologies.
Binance
Senior Staff Engineer - Java at Binance: Develop crypto-related products with autonomy, lead global greenfield projects, and drive transformative infrastructure upgrades.
Uberall
Join Uberall as Senior Backend Engineer and shape the future of location marketing with our SaaS solution
Uberall
Join Uberall as a Senior Backend Engineer and shape the future of location marketing with our innovative SaaS solution.
Wasabi Technologies
Join Wasabi as a Senior QA Engineer and work on challenging projects like S3 features and cockroach DB. Use your expertise in testing methodologies and automation frameworks to ensure high-quality software delivery.
Binance
Senior QA Engineer for Binance's Singapore team, ensuring product safety and quality through rigorous testing and collaboration.
Contentsquare
Join Contentsquare as an Infrastructure Engineer to lead projects in scaling platforms, optimizing pipelines, and building data systems. Utilize skills in Golang, Scala, Terraform, Spark, Kafka, Redis, PostgreSQL, and Singlestore while enjoying benefits like stock options and remote work flexibility.
Canonical
Join Canonical as a Site Reliability Engineer to bring Python engineering skills to operations, manage cloud infrastructure, and drive automation using DevSecOps practices. Gain experience in OpenStack, Kubernetes, and more while working remotely with a talented team focused on innovation and excellence.
Rackspace
Lead global SRE team at Rackspace to ensure high reliability for ObjectRocket platform. Design and implement complex architectural designs, drive automation, and improve system performance. Collaborate with engineers to enhance stability and performance.
Kontakt.io
Join Kontakt.io as a technical expert and help streamline care operations with AI-powered platform
ScienceLogic
Enhance SaaS infrastructure security, ensure FedRAMP compliance, and lead secure cloud system design at ScienceLogic as a Senior Site Reliability Engineer. Collaborate across teams to build robust systems and maintain high availability.
Kontakt.io
Senior Site Reliability Engineer at Kontakt.io, ensuring scalability, availability, and security of cloud-based AI-driven healthcare platform.
Xero
Join Xero as a Software Engineer to create innovative solutions for small businesses, leveraging modern technologies like C#, React, SQL Server, and AWS. Enjoy comprehensive benefits including health insurance, flexible work arrangements, and career growth opportunities.
Rewatch
Join Rewatch as a Senior Software Engineer to design and implement scalable video platform features using Ruby, JavaScript, and SQL. Collaborate with Product Design and support teams while enjoying comprehensive benefits including equity and remote work options.
Testlio
Senior Software Engineer at Testlio: Harness data & AI advancements to drive testing efficiency and shape the future of quality management.
Canonical
Join Canonical as a software engineer to help build the future of Ubuntu Server. Collaborate on open-source projects, maintain packages, and contribute to the development of a leading OS platform used globally in public clouds and enterprise environments.
Quantum Metric
Senior Software Engineer at Quantum Metric, building customer-facing applications using React, GraphQL, D3, and advanced browser APIs.
Enode
Senior Engineer at climate tech startup Enode, building scalable backend components and leading technical initiatives with TypeScript-based codebase.
Splice
We are seeking a Senior Machine Learning Engineer to join our Splice AI & Audio Science team. As a key member of the team, you will design and optimize cutting-edge model architectures for generative audio/music applications, collaborate with other researchers and engineers, and contribute to integrating machine learning models into our products. You will have the opportunity to work on state-of-the-art deep learning techniques, explore new building blocks in generative models, and stay current with the latest advancements in machine learning applied to generative models in the audio domain. Our team is passionate, creative, and committed to using AI in a creator-centric, ethical, and responsible way. With flexible remote work options, $4,000/year travel stipends, and equity in a fast-growing company, we offer a competitive compensation package of $165,000 - $206,000 per year. If you are a seasoned expert with a strong track record in designing, training, evaluating, and deploying machine learning models, we encourage you to apply now.
JOB TITLE: Senior Machine Learning Engineer
LOCATION: Remote / NY
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 WILL DO:
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.
JOB 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).
NICE TO HAVES:
Familiarity with audio signal processing, music information retrieval (MIR), or audio synthesis techniques is a strong plus.
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.
