AI Researcher, Perplexity AI

• 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)

Desirable

• 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:
• 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
• 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
• 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