The roleYou'll build the systems that make GRAI's AI music products work. From backend services and media pipelines to model inference and infrastructure, you'll own hard technical problems end-to-end and help shape the architecture as we scale.
What you'll own- Design, build, test, and maintain production software used in GRAI's AI music products.
- Build backend services, APIs, workers, internal tools, and orchestration systems for media and AI pipelines.
- Work with audio/video processing systems, including formats, codecs, transcoding, metadata, storage, streaming, and delivery.
- Build and optimize systems around model inference, job queues, scheduling, batching, caching, retries, and observability.
What we're looking for- Strong software engineering experience building production systems.
- Strong Python experience.
- Solid understanding of data structures, algorithms, complexity, and practical performance tradeoffs.
- Experience with distributed systems, backend services, APIs, queues, databases, object storage, and cloud infrastructure.
- Ability to debug complex issues across code, infrastructure, network, storage, and service boundaries.
- Experience writing clean, tested, maintainable code.
- Ability to work independently, make good technical decisions, and own projects end-to-end.
Especially relevant experience- Experience with one or more additional languages: Go, Rust, C++, Java, TypeScript, or similar.
- Experience with audio, video, media processing, codecs, containers, streaming, transcoding, FFmpeg, or similar systems.
- Experience with ML infrastructure, model serving, GPU workloads, inference optimization, batching, or distributed training/inference systems.
- Experience with cloud infrastructure, Kubernetes, Docker, Terraform, AWS/GCP/Azure/Nebius, or similar.
- Experience with data pipelines, object storage, large-scale file processing, WebDataset, S3-compatible storage, Spark/Ray/Polars/DuckDB, or similar.
What we offer- High ownership over important technical work
- Be at the forefront of AI-driven music innovation
- Opportunity to work on infrastructure at scale
- Competitive compensation and equity
- Flexibility in how you work
