Member of Technical Staff (AI Researcher)
Perplexity · San Francisco
- Location
- San Francisco
- Employment
- Full time
- Level
- Staff
- Posted
- 3 weeks ago
About this role
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
As published by Perplexity. Applications are handled on their site.
Skills this posting mentions
About Perplexity
Perplexity AI builds AI native search tools. Perplexity Ask, a new search interface that uses OpenAI GPT 3.5 and Microsoft Bing to directly answer any question you ask.
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Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
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