Job Details

Machine Learning Engineer

  2026-05-27     Sonilo     Santa Rosa,CA  
Description:

About the job

Sonilo is a VC-backed AI music generation company building the next generation of soundtrack creation for video. Founded in Silicon Valley, Sonilo helps creators, brands, and platforms instantly generate original music that understands a video's content, pacing, and exact duration — eliminating the need for manual editing, stock music searching, or beat matching. From short-form social content to cinematic storytelling, Sonilo enables anyone to turn silent videos into finished content in seconds through AI-powered music generation built for modern creators.

Role Description

As a Machine Learning Engineer, you will combine hands-on engineering with architectural leadership to design and implement reasoning systems, tool orchestration, and multimodal integrations using cutting-edge large language models (LLMs) and diffusion models.

What You'll Do

Develop next-generation AI systems for video-to-music generation and multimodal creative workflows

Build and optimize AI-native product experiences that understand video content, pacing, emotion, and timing to generate high-quality music experiences

Design scalable model architectures and inference pipelines for multimodal generation

Work closely with product, design, and infrastructure teams to bring cutting-edge generative AI capabilities into production

What You Need To Succeed

Master's or PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field

Demonstrated experience in generative AI, multimodal systems, LLMs, diffusion models, music/audio generation, or AI agent development

Experience building scalable AI systems, model inference pipelines, or real-time AI applications

Strong foundation in machine learning, software engineering, data structures, and algorithms

Excellent problem-solving and analytical skills, with a proactive and ownership-driven mindset

Ability to move quickly and adapt in a fast-paced startup environment where priorities may evolve rapidly and ambiguity is common


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