Responsibilities
- Design, build, and maintain our core ML platform infrastructure as code, primarily using Ansible and Terraform, ensuring reproducibility and scalability across large-scale, distributed GPU clusters.
- Apply SRE principles to diagnose, troubleshoot, and resolve complex system issues across the entire stack, ensuring high availability and performance for critical AI workloads.
- Develop robust internal automation and tooling for ML workflow orchestration, resource scheduling, and platform operations, with a strong focus on software engineering best practices.
- Collaborate with ML researchers and applied scientists to understand infrastructure needs and build solutions that streamline their end-to-end experimentation.
- Evolve and operate our multi-cloud and hybrid (on-prem + cloud) environments, implementing monitoring, alerting, and incident response protocols.
- Participate in on-call rotation to provide support for platform services and infrastructure running critical ML jobs, driving root cause analysis and implementing preventative measures.
- Write high-quality, maintainable code (Python, Go) to contribute to the core orchestration platform and automate manual processes.
- Drive the adoption of modern GPU technologies and ensure smooth integration of next-generation hardware into ML pipelines (e.g., GB200, NVLink, etc.).
Benefits
- Eligible for equity
- Benefits (specifics not detailed)
Additional Information
- Applications accepted until November 8, 2025.
- Equal opportunity employer: does not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
