PerplexityMember of Technical Staff (AI Researcher)
Perplexity is hiring a Member of Technical Staff (AI Researcher) in San Francisco, United States. It pays $220k-$485k a year and Level rates it ; you can apply on Perplexity.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions PyTorch, Megatron and Python among its tools and skills.
- Level classes it as a senior role.
- Perplexity has 130 other open roles on Level.
AI in this role
Research and develop SOTA LLMs, post-training techniques, and agent capabilities at Perplexity.
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
How we rate this
Member of Technical Staff (AI Researcher) at Perplexity rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where llm training was part of your work. What did you do?
- Tell me about a project where reinforcement learning was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, AI Research, LLM Training, Reinforcement learning, and Machine learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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