Perplexity AI에서 AI 연구원을 모집합니다. LLM 및 딥러닝 시스템에 대한 깊은 이해를 바탕으로 모델 학습 및 최적화 업무를 수행합니다. Python, PyTorch 활용 능력이 필수이며, SFT, DPO 등 최신 학습 기법을 활용해 검색 및 에이전트 제품의 성능을 고도화합니다. 연구를 실제 제품으로 구현하는 역량을 갖춘 분을 찾습니다.
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.
Depending on your interests and expertise, you'll work on one of three specialized teams:
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.
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.
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.
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
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
