Perplexity Software Engineer on the Training Infrastructure team building distributed systems for AI workload orchestration and experiment management. Focus on reliability, scalability, and performance in cloud environments.
Responsibilities
Build distributed systems that orchestrate AI workloads across global-scale compute infrastructure
Define novel user and agent interfaces for designing, managing, and launching experiments
Create tools that make experiment results legible to humans and agents
Solve problems at the intersection of AI, distributed systems, and research acceleration
Qualification
BSWhy Perplexity is differentCraftsmanshipOwnershipEntrepreneurshipScholarshipPartnership
Required
2+ years of experience developing and shipping distributed systems for compute-intensive workloads, with a focus on reliability, scalability, and performance.
Proficiency in a general-purpose backend language such as Python, Rust, C++, or Go, and experience with cloud infrastructure and container orchestration, such as AWS and Kubernetes.
Familiarity with reinforcement learning (RL), agent evaluation, or ML infrastructure, and an interest in building systems that accelerate experimentation and model development.
BS, MS, or PhD in Computer Science, Engineering, or a related field, or equivalent practical experience.
Why Perplexity is different
Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious.
Ownership. You identify the problem, design the solution and ship it.
Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users.
Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products.
Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence.