Чётко очерченная роль в заметной AI-продуктовой компании даёт возможность создавать распределённую инфраструктуру обучения и оценки агентов; предпринимательская культура может означать высокий темп работы.
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Высокий темпПередовой AIСамостоятельностьВыше рынка
Оценка от Hirify AI
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Текст:
Hirify AI/Оригинал
TL;DR
Software Engineer (AI Training Infrastructure): Building distributed systems for large-scale reinforcement learning and agent evaluation platforms with an accent on reliability, scalability, performance, and experiment interfaces. Focus on orchestrating AI workloads across global-scale compute infrastructure, making experiment results legible to humans and agents, and accelerating model development.
Location: San Francisco, United States
Salary: $220K–$405K USD annually; equity offered. USD salary ranges apply only to U.S.-based positions.
Company
Perplexity builds AI-native products and state-of-the-art models.
What you will do
Build distributed systems that orchestrate AI workloads across global-scale compute infrastructure.
Develop large-scale reinforcement learning and agent evaluation platforms for training models and optimizing agent harnesses.
Define user and agent interfaces for designing, managing, and launching experiments.
Create tools that make experiment results legible to humans and agents, supporting experiment retrospectives and closed-loop autoresearch.
Solve complex 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.
Experience with cloud infrastructure and container orchestration, such as AWS and Kubernetes.
Familiarity with reinforcement learning, agent evaluation, or machine learning infrastructure.
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.
Culture & Benefits
Focus on craftsmanship and high-quality products for AI-native and AI-curious users.
Ownership of identifying problems, designing solutions, and shipping them.
Entrepreneurial environment with urgency and founder-like initiative.
Opportunities to learn from talented peers and pursue knowledge and product improvement.
Collaborative partnership across teams and disciplines.
U.S. full-time employees receive equity, health, dental, vision, retirement, fitness, commuter, and dependent care benefits; international benefits are tailored to the region of residence.
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