Staff+ Site Reliability Engineer, Safeguards ML Infra

Responsibilities

• Configure, deploy, and verify safeguards for every new model release.
• Serve as the safeguards point of contact during release windows and launch operations.
• Deploy new safety classifiers from research, including canary rollouts, post-deployment validation, and discrepancy investigation.
• Verify safeguards across first-party infrastructure, AWS Bedrock, and Google Cloud Vertex AI, and eliminate configuration drift.
• Automate launch runbooks, manual checks, and one-off deployments into continuous validation and repeatable pipelines.
• Build and maintain a safeguards registry with provenance for production systems, models, platforms, deployment times, and deployers.
• Participate in on-call and operational rotations covering incidents, model provisioning, and time-sensitive launches.
• Use postmortems to drive process and tooling improvements.

Requirements

• Experience owning production change management at scale, including deployment pipelines, configuration management, or canary analysis.
• Experience with high-stakes releases as a launch captain, incident commander, or release owner.
• Meaningful production on-call and incident-response experience.
• Experience reducing operational toil through automation and transitioning manual deployment processes to self-service pipelines.
• Experience operating cloud platforms at scale, particularly AWS and Google Cloud.
• Proficiency in Python.
• Bachelor's degree or equivalent combination of education, training, and experience.
• 8+ years of industry software engineering or site reliability engineering experience.

Nice to Have

• Rust experience.
• Experience running launch or production-readiness reviews across multiple teams.
• Familiarity with LLM inference systems and transformer-based model operations.

Compensation

• Annual salary: $320,000–$485,000 USD.