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AI Research/Machine Learning Engineer (Agent Products)
AI Research/Machine Learning Engineer (Agent Products)NLP PEOPLE • San Francisco, CA, United States
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AI Research / Machine Learning Engineer (Agent Products)

AI Research / Machine Learning Engineer (Agent Products)

NLP PEOPLE • San Francisco, CA, United States
10 days ago
Job type
  • Full-time
Job description

Company

Perplexity AI

Responsibilities

  • Perplexity is seeking experienced AI Research / Machine Learning Engineers and Scientists to own our Agent Products (Answering Agent, Deep Research, the Comet Browser Agent). Applicants should be well versed in all aspects of LLM prompting and training, code execution and tool-calling in order to keep redefining what is possible with advanced retrieval.
  • Design a production and training system that allows for an autonomous LLM-powered agent to perform various tools across web, browsing, retrieval, code execution in order to answer a user’s open-ended prompt / query and return a high quality answer with citations.
  • Partner with the Core Research & Post-Training Team to refine the expansion, reformulation, querying, and summarization of our models against Perplexity’s retrieval index.
  • Devise a well-distributed set of multi-turn evaluations that help hill-climb and capture regressions for our browser and deep research agents.
  • Improve the speed and quality of our codebase and engineering processes to ensure we consistently deliver an amazing product experience.
  • Collaborate with Perplexity GTM leaders as well as a wide breadth of stakeholders (e.g., Motorola, TripAdvisor) to develop integrated product solutions that span across a wide breadth of research verticals like Travel, Retail, etc.

Qualifications

  • Proven research experience with large-scale LLMs and Deep Learning systems
  • Strong post-training skills, familiarity with both supervised and reinforcement learning techniques, including reward formulation and evaluation
  • A strong consumer product intuition, especially for Agent products, with a willingness to unblock oneself at any level of the stack and take ownership of the end-product experience
  • An ability to make tradeoffs in developing an end-to-end agent, including training technique, model architecture, and prompting
  • Minimum of 5 years of working on relevant deep learning research areas
  • Additional details

  • Level of experience : Senior (5+ years of experience)
  • #J-18808-Ljbffr

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