Perplexity currently has 30 active AI-related job listings. The company's hiring is heavily focused on the agents stage, which accounts for 47% of its open AI roles. Engineering is the top function for these positions. The majority of these roles are located in the United States and the United Kingdom. Perplexity is frequently seeking candidates with experience in model serving, agent orchestration, and RAG. Over the last 30 days, there has been a 100% decrease in new AI roles, with 0 new positions posted compared to 19 in the previous 30-day period.
Currently tracking 26 active AI roles, down 12% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $175k–$485k (avg $328k).
Perplexity currently has 31 active AI-related roles in our index. The most common open titles are: Internship - Search Machine Learning Engineer (2), Member of Technical Staff (AI Inference Engineer) (2), Member of Technical Staff (AI Infrastructure Engineer) (2), Engineering Manager (TLM, Agents), Engineering Site Lead. Most positions are in Engineering and Research.
Perplexity's active AI hiring is concentrated in: agents (48%), serving infrastructure (19%), application (16%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Perplexity is hiring AI talent in: United States (20 roles), United Kingdom (7 roles), Serbia (3 roles), Germany (1 role).
Job postings at Perplexity most frequently reference: model serving, llm observability, agent orchestration, rag, recommender systems.
In the past 30 days, Perplexity has posted 7 new AI-related roles. That is a -56% change versus the prior 30 days (16 → 7).
| Title | Stage | AI score |
|---|---|---|
| Member of Technical Staff (AI Researcher) AI Research Scientist/Engineer at Perplexity focused on advancing AI-powered search and agent experiences. The role involves post-training SOTA LLMs using SFT/DPO/GRPO, leveraging query/answer datasets, and developing in-house improvements. Responsibilities include owning full-stack data, training, and evaluation pipelines, building robust training frameworks, and integrating models into the product suite. Experience with large-scale LLMs, Deep Learning, Python/PyTorch, and post-training techniques is required. Nice-to-haves include PhD, experience with agent systems, and personalization. | Post-trainAgent | 9 |
| Member of Technical Staff (Secure Intelligence Institute) Research role focused on advancing security, privacy, and trust in frontier AI systems, developing novel defenses, and building evaluation frameworks, with a strong emphasis on translating research into practical product improvements and publishing findings. |
| AgentEval Gate |
| 9 |