AI Research/Machine Learning Engineer - Agent Products

3 Hours ago • 5 Years + • $200,000 PA - $280,000 PA

Job Summary

Job Description

The AI Research/Machine Learning Engineer will be responsible for designing a production and training system for autonomous LLM-powered agents. They will refine models with the Core Research & Post-Training Team, develop multi-turn evaluations, and improve codebase speed and quality. Collaboration with GTM leaders and stakeholders for integrated product solutions is also expected. The role requires deep understanding of LLMs, post-training techniques, and consumer product intuition. They must have the ability to make tradeoffs in developing an end-to-end agent, including training technique, model architecture, prompting, etc. This role requires someone with 5 years of relevant experience.
Must have:
  • Proven research experience with large-scale LLMs and Deep Learning systems.
  • Strong Post-Training skills with supervised and reinforcement learning techniques.
  • Strong consumer product intuition for Agent products, and ownership of the experience.
  • Understands how to make tradeoffs in developing an end-to-end agent
Perks:
  • Comprehensive health, dental, and vision insurance for you and your dependents.
  • Includes a 401(k) plan.
  • Equity may be part of the total compensation package.

Job Details

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.

Responsibilities

  • Design a production and training system that allows for an autonomous LLM-powered agent performs various tools across web, browsing, retrieval, code execution in order to answer a user’s open-ended prompt / query and returns 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 Evals that help hill-climb and capture regressions for our browser and deep research agents.
  • Improving the speed and quality of our codebase and engineering processes to ensure we consistently deliver an amazing product experience.
  • Collaborating with Perplexity GTM leaders as well as a wide breadth of stakeholders (e.g. Motorola, TripAdvisor, etc.) 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, with a familiarity with both supervised and reinforcement learning techniques, including reward formulation, a good sense for evaluation, etc.
  • A strong consumer product intuition especially for Agent products, with a willingness to unblock one-self at any level of the stack, and take ownership of the end-product experience.
  • Understands how to make tradeoffs in developing an end-to-end agent, including training technique, model architecture, prompting, etc.
  • Minimum of 5 years of working on relevant deep learning research areas.

The cash compensation range for this role is $200,000 - $280,000.

At Perplexity, we've experienced tremendous growth and adoption since publicly launching the world's first fully functional conversational answer engine in 2022. We've grown from answering 2.5 million questions per day at the start of 2024 to around 20 million daily queries in December 2024. We also offer Perplexity Enterprise Pro, which counts leading companies like Nvidia, the Cleveland Cavaliers, Bridgewater, and Zoom as customers.

To support our rapid expansion, we've raised significant funding from some of the most respected technology investors. Our investor base includes IVP, NEA, Jeff Bezos, NVIDIA, Databricks, Bessemer Venture Partners, Elad Gil, Nat Friedman, Daniel Gross, Naval Ravikant, Tobi Lutke, and many other visionary individuals. In 2024, our employee base grew nearly 300%, and we're just getting started.
 
Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.
 
Equity: In addition to the base salary, equity may be part of the total compensation package.
Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.
 

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