Perplexity is an AI-driven search and answer engine that surfaces information from verified sources and offers interactive, topic-specific hubs for users.
Perplexity is seeking top-tier AI Research Scientists and Engineers to advance our AI products and capabilities. We're building the future of AI-powered search and agent experiences through our Sonar models, Deep Research Agent, Comet Agent, and Search products. Join us in creating SOTA experiences that handle hundreds of millions of queries and continue to scale rapidly. Team Structure Depending on your interests and expertise, you'll work on one of three specialized teams: 1. Core Research Team (Horizontal) Focus on generating and improving base models that power all our products. This team works on foundational model capabilities, post-training techniques, building RL infra and infrastructure that benefits the entire organization. 2. Agent Products Team (Vertical) Concentrate on fine-tuning and optimizing models for our Deep Research Agent and Labs/Canvas products. This team bridges research and product, ensuring our agent capabilities deliver exceptional user experiences. 3. Comet Agent Team (Vertical) Dedicated to developing and enhancing our Comet Agent product. This specialized team focuses on the unique requirements and optimizations needed for Comet's specific use cases. Responsibilities Research & Development - Post-train SOTA LLMs using the latest supervised and reinforcement learning techniques (SFT/DPO/GRPO) - Leverage our rich query/answer dataset to scale model performance across Sonar, Deep Research, Comet, and Search products - Stay current with the latest LLM research, especially in model training, optimization, and personalization techniques - Implement preference optimization and personalization capabilities to enhance user experience - Invent in-house improvements and optimizations to enhance SOTA models - Turn research ideas into algorithms and run experiments to launch new models Infrastructure & Implementation - Own full-stack data, training, and evaluation pipelines required for model development - Build robust and effective training frameworks (on top of Megatron/PyTorch) for post-training LLMs - Implement necessary infrastructure and components to support cutting-edge model training at scale - Integrate models seamlessly into our product ecosystem Collaboration - Work closely with engineering teams to integrate models into Perplexity's product suite - Collaborate across teams to ensure cohesive AI experiences throughout our platform - Partner with product teams to understand user needs and translate them into model improvements Qualifications Required - Proven experience with large-scale LLMs and Deep Learning systems - Strong programming skills in Python/PyTorch; versatility is a plus - Experience with post-training techniques and reinforcement learning - Self-starter with a willingness to take ownership of tasks - Passion for tackling challenging problems - Minimum 2-6 years of experience on relevant projects (depending on seniority level) Nice-to-have - PhD in Machine Learning, AI, Systems, or related areas - Experience in post-training LLMs with SFT/DPO/GRPO - C++/CUDA programming skills - Experience building LLM training frameworks - Academic publications and research impact - Experience with agent systems and multi-step reasoning - Background in personalization and preference learning