Member of Technical Staff (Software Engineer, Training Infrastructure)
Join Perplexity's Training Infrastructure team to build distributed systems for AI workloads and enhance model training.
Posted by employer 1 day ago
First seen on Joblaze 16 hours ago
Last verified on the company career page 16 hours ago
What you'll build
- build distributed systems for AI workloads
- define user and agent interfaces for experiments
- create tools for experiment result analysis
Must have
- 2+ years of experience developing distributed systems
- proficiency in a general-purpose backend language
- experience with cloud infrastructure and container orchestration
Nice to have
- familiarity with reinforcement learning
- interest in building systems for model development
Requirements
- Experience
- 2+ years
- Education
- Bachelor's degree
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
In this role, the engineer will focus on developing and maintaining distributed systems that support AI workloads, enhancing the training infrastructure for advanced models. Key skills include proficiency in backend programming languages like Python or Rust, along with experience in cloud services and container orchestration. This position is ideal for candidates with a background in computer science or engineering and at least two years of experience in distributed systems, particularly those interested in AI and research acceleration. The team emphasizes craftsmanship and ownership, fostering a collaborative environment that encourages innovation.
Joblaze insights
Quick facts
- How much experience is required?
- At least 2 years of relevant experience for this Member of Technical Staff (Software Engineer, Training Infrastructure) role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AWS, C++, Go, Kubernetes, Python, Rust.
- What seniority level is this role?
- Perplexity targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Member of Technical Staff (Software Engineer, Training Infrastructure) role at Perplexity.
From the original posting
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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