5 дней назад
Safety Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Safety Engineer (AI): Building production-grade safety infrastructure for detecting and preventing free-tier abuse across multimodal AI platforms with an accent on automated moderation, guardrails, and scalable backend systems. Focus on deploying ML models, designing real-time and batch workflows, and building observable systems that maintain high precision and reliability at scale.
Location: Fully remote globally, with optional access to offices in London, New York, San Francisco, and Warsaw.
Company
ElevenLabs is an AI research and product company developing voice, audio, creative, and conversational AI platforms for millions of users and thousands of businesses.
What you will do
- Design and build scalable backend infrastructure for free-tier abuse detection and AI-powered moderation.
- Architect APIs, data pipelines, and service architectures for real-time and batch safety workflows.
- Implement monitoring, alerting, observability, SLIs, SLOs, and performance benchmarks.
- Partner with ML engineers to deploy research models into production across the product suite.
- Drive technical decisions and contribute to the roadmap for scalable, precise platform guardrails.
Requirements
- Direct experience with free-tier abuse, fraud detection, or fake-account and bot farming at scale.
- 6+ years of backend software engineering experience building production systems at scale.
- Strong experience with distributed systems, APIs, data pipelines, asynchronous Python, and backend frameworks.
- Proficiency with AWS or GCP, Docker, Kubernetes, and CI/CD pipelines.
- Experience with Prometheus, Grafana, monitoring, and building observable systems.
- Experience taking systems from 0 to 1 and deploying or working alongside ML/AI systems in production.
Nice to have
- Trust and Safety, Content Moderation, or Integrity engineering experience.
- MLOps experience, including ML model deployment, monitoring, and versioning.
- Experience with SQL, data analysis tools, Kafka, Redis, real-time streaming, or event-driven architectures.
- Familiarity with React or modern frontend frameworks.
Culture & Benefits
- High-velocity environment with rapid experimentation, autonomous teams, and minimal bureaucracy.
- AI-first approach across engineering, growth, and operations.
- Annual discretionary stipend for professional development.
- Annual stipend for meeting colleagues and an annual company offsite.
- Monthly coworking stipend for employees outside the main hubs.
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