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AI Researcher

AI Researcher

Perplexity AISan Francisco, CA, US
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Job Description

Job Description

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 from some of the world's most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision-making for people and assistive AI wherever decisions are being made. Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that's growing rapidly for one simple reason : everyone can be curious.

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

Compensation & Benefits

Our cash compensation range for this role is $200,000 - $300,000.

Equity : In addition to the base salary, equity is part of the total compensation package.

Benefits : 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.

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