Zapier
501 - 1000 employees
Founded 2011
☁️ SaaS
⚡ Productivity
🤝 B2B
💰 Secondary Market on 2021-04
SaaS • Productivity • B2B
Zapier is a leading automation platform that enables users to connect and automate workflows across more than 7,000 applications. Known for its no-code approach, Zapier empowers individuals and teams to streamline tasks by creating automated processes called "Zaps," which link triggers and actions between different apps. The platform is trusted by millions of users globally, including 87% of Forbes Cloud 100 companies, offering solutions that enhance productivity and efficiency in various business functions.
Applied AI Engineer
🕒 June 23
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Zapier
501 - 1000 employees
Founded 2011
☁️ SaaS
⚡ Productivity
🤝 B2B
💰 Secondary Market on 2021-04
SaaS • Productivity • B2B
Zapier is a leading automation platform that enables users to connect and automate workflows across more than 7,000 applications. Known for its no-code approach, Zapier empowers individuals and teams to streamline tasks by creating automated processes called "Zaps," which link triggers and actions between different apps. The platform is trusted by millions of users globally, including 87% of Forbes Cloud 100 companies, offering solutions that enhance productivity and efficiency in various business functions.
📋 Description
• Contribute to shared AI Platform capabilities supporting teams building with machine learning and generative AI • Work mostly in TypeScript & Python • Help develop and maintain core services such as the LLM proxy server, platform APIs, and reusable tooling • Build and improve parts of the LLM Ops and ML Ops stack • Help design and implement systems improving performance, reliability, safety, and cost efficiency of AI-powered experiences • Collaborate closely with engineers across product, infra, and data teams • Evaluate emerging tools, models, and patterns in the AI ecosystem
🎯 Requirements
• 4+ years of experience in software engineering • At least 1 year of experience in LLM Ops, ML Ops, or adjacent platform/infrastructure work • Experience contributing to backend systems, developer tooling, internal platforms, or infrastructure that supports other engineers • Experience of working through the full lifecycle of building, testing, deploying, and scaling ML/LLM architectures • Thoughtful about engineering trade-offs in production systems. • Enjoy working collaboratively and learning from others
🏖️ Benefits
• Offers Equity • Offers Bonus
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