Senior Infrastructure Engineer in AI/Music Tech startup
Who we are
AIMS is a music-tech scaleup providing leading AI-powered music search and discovery solutions. We work with the world’s biggest music and media companies — including Warner Chappell PM, Universal PM, Hipgnosis and 60+ others. We’re entirely self-funded and profitable, operating as a remote-first team of music and tech lovers based all over the world.
Our story has been featured in Forbes and CzechCrunch.
Why we need you
As our ML research infrastructure expands, we need an experienced infrastructure engineer to architect and manage our on-prem computing environment. You’ll be responsible for designing, implementing, and maintaining the GPU clusters, distributed storage systems and monitoring infrastructure that powers our core ML research — the foundation of all AIMS technologies and products. Your work will be essential in enabling our research team to efficiently train ML models, process large datasets, and improve the AI technologies our business depends on.
What we use
- Infrastructure: Ceph, Ansible, Linux, NVIDIA GPUs, Prometheus, Grafana, GitLab, MongoDB, Elasticsearch, Jupyter, Dagster, Docker, Kubernetes, Python, shell
- ML Stack (what you'll interact with): PyTorch, CUDA, Hugging Face, NumPy, scikit-learn, MLflow, FastAPI, Flask, Ray
You’ll fit right in if you’ve mastered:
- Infrastructure automation and configuration management (Ansible or similar)
- Managing distributed storage systems (Ceph or similar) — you understand their architecture, can optimize and troubleshoot them
- Designing and managing high-performance computing clusters for parallel computation applications
- Monitoring and observability tools (Prometheus, Grafana) and best practices
- Hardware architecture — you’re comfortable configuring and tuning high-performance systems
- Containerization and container orchestration (Docker, Kubernetes)
- Networking principles — you can design robust network architectures
- Linux system administration and performance tuning
- Security best practices in IT infrastructure
- English — you’re good enough to communicate effectively with the team
- Czech — you’re comfortable discussing technical topics with Czech-speaking contacts
What you don't need to know, but we appreciate if you do or if you're willing to learn
- Good understanding of machine learning principles and frameworks
- Write functional Python code and are comfortable developing custom management tools
- Knowledge of NVIDIA GPUs and experience optimizing and scaling GPU-accelerated ML workloads
- Experience with database administration and understand scaling patterns
- Experience with vector databases and search systems
- Experience with modern MLOps and CI/CD pipelines
- Knowledge of Kubernetes and container orchestration at scale
- Experience with cloud platforms (GCP, AWS, Azure) and cloud DevOps practices
- You like music :)
What we offer
- Competitive salary based on skills and experience
- Friendly teammates (we won't even judge you for using light mode in your IDE)
- Opportunity to build modern ML infrastructure and see the direct impact of your work
- Chance to be at the forefront of the AI revolution in the music business
- Both on-site and remote work possible (our office is in Prague 7 - Letná)
- Occasional on-site presence needed for datacenter access
Are you interested in ML infrastructure and scalable AI systems? Meet our Head of Research Viktor and ask anything you'd like to know.