Safety Engineer

Requirements

• About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology.
• We launched in January 2023 with the first human-like AI voice model.
• ElevenAPI gives developers access to our leading AI audio foundational models.
• AI first: We use AI to move faster with higher-quality results.
• Excellence everywhere: Everything we do should match the quality of our AI models.
• What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.
• About the role We're looking for an experienced AI Safety Engineer to drive the deployment and operationalization of automated moderation and guardrail systems that protect our platform and users across a multimodal space.
• You'll work alongside a team of ML and full stack engineers to build production-grade safety infrastructure from the ground up.
• You'll bridge the gap between ML research and production-grade systems, ensuring our safety infrastructure is robust, observable, and scalable.
• What you'll do: Design and build scalable backend infrastructure for content moderation, abuse detection and agents guardrails, deploying AI/ML models into production systems Architect robust APIs, data pipelines, and service architectures supporting real-time and batch moderation workflows Implement comprehensive monitoring, alerting, and observability systems; establish SLIs, SLOs, and performance benchmarks Partner with ML engineers to translate research models into production-ready systems and
• experience: distributed systems, APIs, data pipelines, and Python expertise (asynchronous Python, backend frameworks) Infrastructure & DevOps proficiency: cloud platforms (AWS/GCP), containerization (Docker/K8s), CI/CD pipelines Observability mindset with
• experience in monitoring tools (Prometheus, Grafana) and building observable systems Track record of taking products or systems from 0→1 with measurable impact, including deploying or working alongside ML/AI systems in production Bonus: Trust & Safety, Content Moderation, or Integrity engineering experience MLOps
• experience: deployment, monitoring, and versioning of ML models
• Experience with SQL, data analysis tools, real-time streaming systems (Kafka, Redis), or event-driven architectures Familiarity with React or modern frontend frameworks Location This role is remote and can be executed globally.