Member of Technical Staff (Software Engineer, Training Infrastructure)

Engg; San Francisco (CA); On-site; USD 220,000 - 405,000; Full time

Job summary

Perplexity in San Francisco is seeking a Member of Technical Staff (Software Engineer, Training Infrastructure) to join the Training Infrastructure team. You will help build distributed systems that orchestrate AI workloads across global compute resources and define interfaces for experiments.

A strong candidate will have 2+ years deploying and shipping distributed systems, and experience with Python, Rust, C++, or Go, plus AWS and Kubernetes.

Qualifications

• 2+ years of experience developing and shipping distributed systems for compute-intensive workloads, with focus on reliability, scalability, and performance.
• Familiarity with RL, agent evaluation, or ML infrastructure, and interest in accelerating experimentation and model development.
• BS, MS, or PhD in Computer Science, Engineering, or related field, or equivalent practical experience.

Responsibilities

• Build distributed systems that orchestrate AI workloads across large-scale compute infrastructure.
• Define and implement interfaces for designing, managing, and launching experiments.
• Create tooling to make experiment results legible to humans and agents for retrospectives and closed-loop research.

Skills

Distributed systems

Backend languages (Python/Rust/C++/Go)

Cloud & Kubernetes

RL/ML infrastructure

Education

BS/MS/PhD in CS/Engineering

Tools

Python

Rust

C++

Go

AWS

Kubernetes

Job description

# Member of Technical Staff (Software Engineer, Training Infrastructure)Perplexity · San FranciscoLocation: San FranciscoSalary: $220K - $405KExperience: 2+ yearsFunding: $1.5BPosted: Oct 24, 2026Perplexity is hiring a Member of Technical Staff (Software Engineer, Training Infrastructure) based in San Francisco. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.Apply directly at Perplexity## Role detailsPerplexity 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.