AI Researcher

Perplexityai

Apply to this job
New York City Palo Alto Until 8/23/2026 H-1B sponsor history First posted November 2, 2025 Last posted November 2, 2025
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.

 

About this role

Summary

Research and develop large language models, optimize training, and integrate AI into products.

Job title

AI Researcher

Experience level

2-6 years

Industry

software

Location requirements

Remote work allowed in New York City, Palo Alto, or San Francisco.

Salary

$200,000 - $300,000

Visa sponsorship

H-1B sponsor history

Management role

No

Skills & keywords

Required skills

pythonpytorchlarge language modelsreinforcement learningpost-training techniques

Preferred skills

c++cudaresearch publicationsagent systemsmulti-step reasoning

Specializations

large language modelsdeep learningreinforcement learningmodel trainingpersonalization
Locations

Structured locations inferred from the posting.

New York, NY, USA

Remote City

Palo Alto, CA, USA

Remote City

San Francisco, CA, USA

Remote City