AI Researcher

Details

Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world’s leading AI platforms. Perplexity has raised over $1B in venture investment and aims to build accurate, trustworthy AI that powers decision-making and assistive AI. The company handles hundreds of millions of queries monthly and is scaling its products and research capabilities.

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 rich query/answer datasets 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 the 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 the platform.
• Partner with product teams to understand user needs and translate them into model improvements.

Requirements

Required

• Proven experience with large-scale LLMs and Deep Learning systems.
• Strong programming skills in Python and PyTorch.
• 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.

Benefits

• Cash compensation range: $200,000 - $300,000 per year.
• Equity is part of the total compensation package.
• Comprehensive health, dental, and vision insurance for you and your dependents.
• Includes a 401(k) plan.
• Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.