Perplexity

Engineering Manager to lead and grow an AI Agents team focused on building agentic experiences within the Comet ecosystem. The role involves technical leadership, developing AI models and infrastructure, driving product reliability and evaluation, and managing a growing team to advance the capabilities of AI agents for users.

Engineering Manager for AI Research & Model Training at Perplexity, leading a team to develop and train state-of-the-art large language models using advanced techniques like RL, SFT, and preference-based methods. The role involves owning data, training, and evaluation pipelines, and integrating models into products, requiring significant experience in large-scale AI model development and team leadership.

Engineering Manager for AI Inference team focused on building and scaling the infrastructure for Perplexity's AI capabilities, including deploying and optimizing large sparse/MoE models, developing inference APIs, and improving system reliability and observability.

AI Infrastructure Engineer responsible for building, deploying, and optimizing large-scale AI training and inference clusters using Kubernetes and Slurm on AWS. The role involves managing HPC environments, developing orchestration systems, implementing resource scheduling, and building monitoring solutions for ML workloads.

AI Inference Engineer responsible for building and running the inference engine for Perplexity's models, focusing on performance, reliability, and cost-efficiency across various model architectures and GPU hardware. The role involves migrating CUDA kernels to CuTe DSL, developing a Rust-based serving runtime, and optimizing performance from network ingress to GPU kernels.

AI Research Lead at Perplexity to drive research strategy and lead development of in-house Online LLMs (Sonar models). Role involves setting macro research direction across modalities, mentoring researchers, and scaling model performance using query/answer datasets.

AI Research Scientist/Engineer at Perplexity focused on advancing AI-powered search and agent experiences. The role involves post-training SOTA LLMs using SFT/DPO/GRPO, leveraging query/answer datasets, and developing in-house improvements. Responsibilities include owning full-stack data, training, and evaluation pipelines, building robust training frameworks, and integrating models into the product suite. Experience with large-scale LLMs, Deep Learning, Python/PyTorch, and post-training techniques is required. Nice-to-haves include PhD, experience with agent systems, and personalization.

Perplexity is looking for an AI Software Engineer to join their Agents team, focusing on building agentic experiences within their AI products. The role involves designing AI agents, training action/decision models, ensuring excellent user experiences across platforms, developing secure agentic capabilities, and optimizing data representations for agent-environment interaction. The engineer will drive AI capabilities, leverage AI models and infrastructure, and ensure high quality in AI agent performance and user experience.

Seeking an ML Research Engineer to advance search technologies, focusing on retrieval and ranking. Responsibilities include architecting and building core search platform components, designing/training/optimizing large-scale deep learning models (PyTorch, distributed training), conducting research in representation learning (contrastive, multilingual, multimodal), deploying models, and building RAG pipelines. Requires deep understanding of search/retrieval, large-scale search/recommender systems experience, PyTorch proficiency, expertise in representation learning, and a strong publication record.

Research role focused on advancing security, privacy, and trust in frontier AI systems, developing novel defenses, and building evaluation frameworks, with a strong emphasis on translating research into practical product improvements and publishing findings.

The Model Behavior Architect will design and optimize context engineering strategies and evaluation systems for Perplexity's AI products. This role involves pressure-testing model capabilities, ensuring behavioral consistency, and supporting model launches by identifying and fixing failure modes. The goal is to deliver high-quality user experiences by improving model behavior and quality through systematic evaluation and iteration.

Internship role focused on advancing search quality through research and engineering of large-scale deep learning models, representation learning, and RAG pipelines. Involves distributed training, optimization, and evaluation of retrieval and ranking models.

Applied AI Engineer to design, build, and iterate on cutting-edge agents powering the core experience in Perplexity Computer. This role involves developing frontier context layer applications, personalization, recommendations, and monetization applications, as well as building agent capabilities. The engineer will own the full model lifecycle from research to production, including data analysis, modeling, evaluation, A/B testing, and iterative improvement, and will also build an auto research harness for agent exploration. Collaboration with cross-functional teams and staying updated on AI innovation are key.

Machine Learning Engineer focused on building and deploying search technologies, including retrieval, ranking, and RAG pipelines, with a focus on LLMs.

This role is for a software engineer on the 'Computer' team at Perplexity, focusing on building and owning product and platform systems for agentic AI. The engineer will lead features end-to-end, iterate on hard problems, and build systems that handle AI nuances like agents, context, evaluation, and personalization. The role requires strong software engineering experience, production system building, and product judgment, with a preference for experience in LLMs, agents, retrieval systems, personalization, or evaluation frameworks.

AI Infrastructure Engineer responsible for building, deploying, and optimizing large-scale AI training and inference clusters using Kubernetes and Slurm on AWS. The role involves managing HPC environments, developing orchestration systems, implementing resource scheduling, and building monitoring solutions for ML workloads.

AI Inference Engineer responsible for building and running the inference engine for Perplexity's models, focusing on performance, latency, and cost optimization across various model architectures. The role involves supporting transformer-based models, migrating GPU kernels, developing a Rust-native serving runtime, and ensuring reliability and observability of the inference infrastructure.

Software Engineer to build AI Foundation & Platform, focusing on end-to-end AI data, evaluation, and personalization infrastructure for agent products. Responsibilities include designing scalable data pipelines, high-performance infrastructure for personalization features, and a multi-modal evaluation platform. Requires strong programming, data engineering, and distributed systems experience, with familiarity in cloud services and ML/AI engineering support.

AI Security Engineer responsible for designing and implementing mechanisms to secure AI systems, including LLM APIs, agents, and self-hosted models, against adversarial threats. This involves hands-on remediation, threat modeling, and security assessments.

Internship role focused on improving search quality through retrieval, ranking, and RAG pipelines, involving model experimentation, implementation, training, and deployment support.

This role focuses on building AI systems to revolutionize data science workflows. The core responsibilities include developing AI agents for autonomous data analysis, making data warehouses AI-readable, automating data lifecycle management with self-healing pipelines, and creating AI-powered experiment analysis tools. The goal is to transform the data team into an AI-native product team, enabling significant leverage and industry-leading practices.

This role focuses on building AI systems to revolutionize how data science is performed. The core responsibilities include developing AI agents for autonomous data analysis (hypothesis generation, query execution, interpretation, recommendations), making the data warehouse AI-readable, automating data lifecycle management with self-healing pipelines, and creating AI-powered experiment analysis tools. The goal is to transform the data team into a product team by building internal data products that leverage AI, enabling 10x operational efficiency.

This role focuses on building and maintaining automated evaluation pipelines to assess the quality of answers generated by LLMs in Perplexity's search engine and other products. It involves designing evaluation sets, developing VLM-based solutions for visual rendering assessment, and adapting public benchmarks. The goal is to directly shape product changes by providing key evaluation metrics.

Engineering Site Lead for Perplexity in London, responsible for establishing and scaling the office, building and managing infrastructure and AI infrastructure teams, and driving technical excellence in AI systems. The role involves direct people management, setting technical direction, and ensuring robust systems for AI/ML workloads.

Forward Deployed Engineer role focused on integrating Perplexity's AI API Platform and Perplexity Computer (agentic workflows) into enterprise customer systems. The role involves designing, building, and deploying end-to-end AI integrations, automating business workflows, and optimizing performance, security, and customer impact. Requires strong software engineering skills, experience with LLM-powered systems, and customer-facing deployment.

Product Data Scientist focused on search quality, developing data-driven insights, designing and analyzing A/B tests, and creating pipelines for ranking quality, including data labeling with human and LLM feedback.

Software Engineer, Data Flywheel role focused on building systems and pipelines for accessing and utilizing eval verdicts, turning raw signals into datasets, and creating a simulator pipeline for user interactions. This role emphasizes data trust through monitoring and quality checks, operating within a high-impact team to improve Answer Quality.

This role focuses on leveraging AI tools and agents to improve the efficiency and delivery cadence of various teams within Perplexity, including engineering, research, and operations. The candidate will be responsible for identifying opportunities to use AI, making internal systems AI-legible, and building both prototypes and production systems to accelerate development and operations. It's a hybrid role blending AI product development, infrastructure/platform engineering, and developer experience.

Internship program focused on improving the AI inference engine and serving stack for Perplexity products, optimizing latency and throughput on large GPU clusters, and supporting new models and inference optimizations.

Internship role focused on improving search quality through retrieval and ranking models, including RAG pipelines, and contributing to the deployment and monitoring of these models. The role involves experimentation and collaboration with various teams.