Applied ML Engineer
About Splash At Splash, our mission is to make music creation accessible for everyone. Since 2017, we’ve been pioneering the intersection of artificial intelligence and music, creating tools that empower young creators and music enthusiasts. Our experiences, particularly on platforms like Roblox, have inspired millions to engage with music in new ways. Backed by leading investors such as Amazon's Alexa Fund and Khosla Ventures, we are expanding rapidly, assembling a diverse team of musicians, engineers, and creatives passionate about shaping the future of music and AI. About the Role We are seeking an Applied Machine Learning Engineer with a strong focus on practical solutions and software development (ability to work on both open-ended research problems and production-ready API code). In this role, you'll leverage off-the-shelf tools and custom-built ML models to solve challenges in music product development and improve manual music processes. This position is ideal for engineers with demonstrable experience building functional, production-ready models and who are passionate about user experience and Product. Key Responsibilities: Design and implement ML algorithms to enhance music creation tools and solve various user problems in line with product goals. Identify and implement off-the-shelf ML and AI tools to solve practical problems efficiently. Understand the requirements of running models in production, including domain shift testing, QA, A/B testing and so on. Maintain production-ready code with considerations for how solutions fit the product and enhance the user experience. Build scalable, maintainable data pipelines to handle audio and other unstructured data.Collaborate with Product and Engineering teams to ensure seamless integration of ML solutions into production systems. Evaluate, deploy, and fine-tune pre-trained models for tasks like audio analysis, melody generation, and process automation. Uphold ethical AI practices, ensuring fairness and responsible AI use in music-related applications. What You Bring Proven software development experience, ideally in Python (other languages a plus).Experience implementing and deploying ML models, using PyTorch framework. Familiarity with AWS cloud environment for deploying and scaling ML solutions. Ability to preprocess and model unstructured data, especially audio. A strong focus on applied problem-solving, with a practical approach to integrating existing tools and systems. A good understanding of music, production, or audio technology processes (or a strong interest in music)Familiarity with GenAI architectures like transformers, LLMs, or diffusion models. Proactive nature, ability to creatively solve problems you face and bring new ideas to the team. Clear and effective communication with technical and non-technical stakeholders. Ability to work independently and remotely while collaborating closely with cross-functional teams. Why Join Us? Work directly with industry veterans from Spotify, Soundcloud, Twitch, and YouTube. Be part of a passionate, innovative team redefining music creation and interaction - we love music! Small, dynamic team backed by leading investors including Amazon’s Alexa Fund, Khosla Ventures, BITKRAFT Ventures and King River Capital. Flexible work arrangements, working remotely with a global team with regular trips to our HQ in Brisbane AustraliaThe opportunity to contribute to cutting-edge music technology. Our Commitment to Diversity, Equity, and Inclusion Music has the incredible ability to bridge divides and bring people together, regardless of their background or identity. Like the industry we work within, diversity, equity and inclusion are at the heart of everything we do. We are committed to creating an inclusive environment where everyone feels valued, respected, and empowered. We actively seek out and welcome voices from all backgrounds and believe that diverse perspectives fuel our creativity and drive success. Application Process Please apply or feel free to send your resume and email to our Head of People & Culture, [email protected] PDF Resume Preferred For more info visit splashmusic.com Originally posted on Himalayas