Role details
- Perplexity is seeking software engineers to join our Training Infrastructure team. We're responsible for the large-scale RL and agent evaluation platforms that enable Perplexity to train state-of-the-art models and optimize agent harnesses.
- We are full-stack engineers with a broad remit.
- If you join us, you'll build the distributed systems that orchestrate AI workloads across global-scale compute infrastructure.
- You'll also define novel user and agent interfaces for designing, managing, and launching experiments.
- You'll create tools that make experiment results legible to humans and agents alike, enabling everything from ad-hoc experiment retrospectives to closed-loop autoresearch.
And much more!
A strong candidate will possess both experience and passion for solving difficult problems at the intersection of AI, distributed systems, and research acceleration.
QUALIFICATIONS
- 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.