
Member of Technical Staff (Software Engineer, Training Infrastructure)
San Francisco, CA at a glance
- Rent
- #2 of 51$2,680/mo+46% vs US avg
- Weather
- #17 of 51295 mild days0 hot · 0 cold
- Income tax
- #1 of 5113.3% top rateCalifornia
What you need
- 2+ yrs distributed systems for compute-intensive workloads
- Proficiency in Python, Rust, C++, or Go
- Experience with AWS and Kubernetes
- Familiarity with RL, agent evaluation, ML infrastructure
- BS/MS/PhD in CS/Engineering or equivalent experience
What you'll do
- Build distributed systems orchestrating experiments at global scale
- Define user/agent interfaces for experiment design and launch
- Create tools for experiment result legibility and analysis
- Enable closed-loop autoresearch and experiment retrospectives
- Optimize large-scale RL and agent evaluation platforms
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 create, refine, and optimize services that handle the complexity of running these workloads reliably at scale.
We are full-stack engineers with a broad remit. If you join us, you’ll build the distributed systems that orchestrate those experiments across global-scale compute infrastructure. You’ll also define the 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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About Perplexity
Perplexity is building the most powerful answer engine — powering curiosity with answers backed by up-to-date sources. Their AI-powered search platform provides accurate, cited answers to complex questions.
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