AI Researcher (Member of Technical Staff)

Perplexity AI; New York (NY); On-site; USD 170,000 - 230,000; Full time

Job summary

Perplexity AI in New York is seeking top-tier AI Research Scientists and Engineers to advance our Sonar models, Deep Research Agent, Comet Agent, and Search products. You’ll join one of three specialized teams and work on code and models that power hundreds of millions of queries.

Responsibilities include post-training SOTA LLMs, leveraging RL and supervised techniques, building robust training pipelines on Megatron/PyTorch, and collaborating with product teams to translate research into

Qualifications

• PhD in Machine Learning, AI, Systems or related field.
• Experience with large-scale LLMs and Deep Learning systems.
• Strong programming skills in Python/PyTorch; C++/CUDA is a plus.

Responsibilities

• Post-train SOTA LLMs using supervised and reinforcement learning techniques (SFT/DPO/GRPO).
• Leverage datasets to scale model performance across products.
• Build and maintain training pipelines and infrastructure for model development.
• Collaborate with product teams to translate research into scalable AI experiences.

Skills

Python

PyTorch

C++/CUDA

ML Research

Deep Learning

Reinforcement Learning

Distributed Training

Self-starter

Education

PhD in ML/AI/Systems

Tools

Megatron

CUDA

Job description

• 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:
• 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:
• 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
• 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
• 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

• Minimum 2-6 years of experience on relevant projects (depending on seniority level)
• Passion for tackling challenging problems
• Proven experience with large-scale LLMs and Deep Learning systems
• Experience with post-training techniques and reinforcement learning
• Strong programming skills in Python/PyTorch; versatility is a plus
• Self-starter with a willingness to take ownership of tasks
• 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
• Experience with agent systems and multi-step reasoning
• Academic publications and research impact
• Background in personalization and preference learning