Member of Technical Staff (Software Engineer, Training Infrastructure)

Candidate; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Perplexity is seeking software engineers to join our Training Infrastructure team, building distributed systems that orchestrate AI workloads across global-scale compute infrastructure. You’ll design interfaces to manage experiments and create tools that render results accessible to humans and agents alike.

A strong candidate will have experience solving hard problems at the intersection of AI, distributed systems, and research acceleration, with a passion for craftsmanship and ownership.

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.

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 alike, enabling retrospectives and autoresearch.
• Collaborate on shaping the platform at the intersection of AI, distributed systems, and research acceleration.

Skills

Distributed systems

Backend development

Python

Rust

C++

Go

AWS

Kubernetes

Education

BS/MS/PhD in Computer Science or Engineering

Tools

Kubernetes

AWS

Job description

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.