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Perplexity
Actively Hiring19 open positions matching criteria
Member of Technical Staff (General Software Engineer, Infrastructure)
Platform & Infrastructure
About the Role The Infrastructure team builds and operates the foundational systems behind Perplexity’s products. At Perplexity, infrastructure sits on the critical path of every answer, supporting real-time search, retrieval, model serving, and agent workloads where latency, reliability, and rapid iteration directly shape the user experience. This role is for strong infrastructure engineers whose experience spans multiple domains and who are energized by cross-cutting problems that do not fit neatly within a single platform team. You do not need to be a specialist in every area. Scope ranges from owning major production systems to setting technical direction across teams, leading complex infrastructure programs, and shaping infrastructure strategy across the organization. If a specialized Cloud Infrastructure, Storage Platform, Backend Platform, Data Platform, Connector Platform, or AI Acceleration role clearly matches your expertise and interests, apply directly to it. If your experience spans several infrastructure domains or you are most energized by cross-cutting systems problems, apply here. Submit one application, and we will consider you across the Infrastructure organization. Key Responsibilities Own cross-cutting infrastructure problems that span compute, storage, networking, data, deployment, and reliability, including eliminating bottlenecks across retrieval and serving paths, building shared abstractions across deployment environments, and resolving failure modes that cross platform boundaries. Design, build, and operate distributed infrastructure supporting Perplexity’s consumer, AI, and enterprise workloads, owning systems from architecture through production operation. Identify gaps between existing platforms and build shared abstractions, automation, and tooling that make infrastructure easier and safer to use. Improve system performance, availability, scalability, and cost-efficiency across online request traffic and background workloads. Debug complex production issues across service and infrastructure boundaries, then turn the findings into durable architectural improvements. Set technical direction for complex infrastructure systems, lead high-impact programs across teams, and establish durable technical standards through collaboration with infrastructure, product, AI, and security partners. Qualifications 4+ years of professional software engineering experience building and operating production backend, platform, or distributed systems. A track record of owning complex production systems end to end and delivering sustained technical impact across teams. Demonstrated ability to set technical direction, lead through influence, and raise the engineering bar through architecture, design reviews, and mentorship. Strong software engineering skills in Python or other systems or backend languages such as Go, Rust, C++, or Java. Meaningful experience across at least two infrastructure domains, such as cloud platforms, distributed systems, Kubernetes, storage, databases, networking, data systems, developer infrastructure, or production reliability. Ability to develop depth quickly in unfamiliar systems, reason across software and infrastructure layers, and drive production incidents from diagnosis through durable resolution. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.
View more...Member of Technical Staff (General Software Engineer, Infrastructure)
Platform & Infrastructure
About the Role The Infrastructure team builds and operates the foundational systems behind Perplexity’s products. At Perplexity, infrastructure sits on the critical path of every answer, supporting real-time search, retrieval, model serving, and agent workloads where latency, reliability, and rapid iteration directly shape the user experience. This role is for strong infrastructure engineers whose experience spans multiple domains and who are energized by cross-cutting problems that do not fit neatly within a single platform team. You do not need to be a specialist in every area. Scope ranges from owning major production systems to setting technical direction across teams, leading complex infrastructure programs, and shaping infrastructure strategy across the organization. If a specialized Cloud Infrastructure, Storage Platform, Backend Platform, Data Platform, Connector Platform, or AI Acceleration role clearly matches your expertise and interests, apply directly to it. If your experience spans several infrastructure domains or you are most energized by cross-cutting systems problems, apply here. Submit one application, and we will consider you across the Infrastructure organization. Key Responsibilities Own cross-cutting infrastructure problems that span compute, storage, networking, data, deployment, and reliability, including eliminating bottlenecks across retrieval and serving paths, building shared abstractions across deployment environments, and resolving failure modes that cross platform boundaries. Design, build, and operate distributed infrastructure supporting Perplexity’s consumer, AI, and enterprise workloads, owning systems from architecture through production operation. Identify gaps between existing platforms and build shared abstractions, automation, and tooling that make infrastructure easier and safer to use. Improve system performance, availability, scalability, and cost-efficiency across online request traffic and background workloads. Debug complex production issues across service and infrastructure boundaries, then turn the findings into durable architectural improvements. Set technical direction for complex infrastructure systems, lead high-impact programs across teams, and establish durable technical standards through collaboration with infrastructure, product, AI, and security partners. Qualifications 4+ years of professional software engineering experience building and operating production backend, platform, or distributed systems. A track record of owning complex production systems end to end and delivering sustained technical impact across teams. Demonstrated ability to set technical direction, lead through influence, and raise the engineering bar through architecture, design reviews, and mentorship. Strong software engineering skills in Python or other systems or backend languages such as Go, Rust, C++, or Java. Meaningful experience across at least two infrastructure domains, such as cloud platforms, distributed systems, Kubernetes, storage, databases, networking, data systems, developer infrastructure, or production reliability. Ability to develop depth quickly in unfamiliar systems, reason across software and infrastructure layers, and drive production incidents from diagnosis through durable resolution. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.
View more...Internship Program Berlin Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office. Responsibilities Relentlessly push search quality forward — through models, data, tools, or any other leverage available. Train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models. Conduct research in representation learning, including contrastive learning, multilingual, evaluation, and multimodal modeling for search and retrieval. Build and optimize RAG pipelines for grounding and answer generation. Qualifications Understanding of search and retrieval systems, including quality evaluation principles and metrics. Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models. Interested in representation learning, including contrastive learning, dense & sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization and robust evaluation. Publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR).
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