You and the process

With a person
Anna, in-house recruiter
9 years hiring engineers
30 minutes with a real recruiter
They read your CV with you, on a call, and say where the offers are being lost.
Didn’t find what you were looking for? Tell us what to build
Perplexity

Member of Technical Staff (Software Engineer, Training Infrastructure)

  • Office
  • 6+ years

Salary

$220,000 - 405,000/ year

AI summary

For members

The whole posting in a few lines. Sign up to read it here and on every role you open.

Sign Up to Read

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.

Requirements

  • 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.

Where you’d work

From the office

The office

About the company

Perplexity

  • Industry: AI

Office in San Francisco, United States

Also hiring in New York City, United States, Washington D.c., United States, London, United Kingdom and 3 more places

2 of their 27 open roles are remote

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 21 checks run
  • 3 red flags

Still hiring?

14 checks

No red flags

How crowded?

7 checks

3 red flags

Fits Me

How well does this role fit you?

Answer a few questions or drop your CV, and every role gets a fit score with the reasons, this one first.

  • Your field
  • Level
  • Stack
  • Work model
  • Salary floor
  • Must-haves
Details12 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • Go
  • AWS
  • Kubernetes
  • C++
  • Rust
Seniority
Staff
Type
Full-time
Industry
AI
Specialty
Backend
Region
United States
Show 6 more factsShow less

Role

Category
Development
Specialty
Backend
Seniority
Staff
Experience
2+ years
Tech stack
  • Python
  • Go
  • AWS
  • Kubernetes
  • C++
  • Rust

Location

Work model
Office
Region
United States
Office
  • San Francisco, United States

Compensation

Salary
$220,000 - 405,000 / year
Pay period
Annual

Employment

Type
Full-time

Company

Industry
AI

Something wrong with this vacancy?

Similar vacancies

Share this vacancy

What's wrong with it?

The employer never sees who reported.

Reason