perplexity

Member of Technical Staff (Software Engineer, Training Infrastructure)

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Posted within 60 days ·

  • Workplace not specified
  • FullTime
  • AI Research & Systems
  • San Francisco
Work arrangement
Not stated
Employment
FullTime
Stated compensation
USD 220,000–405,000 1 YEAR
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Requirements

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Minimum experience (years)
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“2+ years of experience developing and shipping distributed systems for compute-intensive workloads, with a focus on reliability, scalability, and performance.”
See matched passage in original description ↓
Employment type
FullTime
Compensation
USD 220,000–405,000 1 YEAR
8 fields not stated in this posting
Remote policy
Unclear
Employer sponsorship
Not specified
Geographic scope
Not specified
Degree requirement
Not specified
Security clearance
Not mentioned
Timezone / hours
Not specified
Citizenship requirement
Not mentioned
Work authorization
Not specified

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READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

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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.
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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.
Original formatting and links

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.

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