Tech Lead - AI Engagement

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.

Perplexity is seeking an experienced Tech lead to help drive the user engagement to next level. In this role, you'll work across different areas across personalization, discovery, agents and evaluations to use AI/ML techniques to drive user engagement at the Perplexity.

Responsibilities

• Lead the research, design, and implementation of an E2E engagement platform which powers different AI applications at Perplexity. Define the future of Perplexity’s AI & ML systems by transforming Perplexity into an engagement powerhouse.


• Collaborate with product, search, browser, and other AI teams to implement compatible and cross-platform solutions to increase user retention.


• Stay abreast of the latest advancements in AI, applying new research, frameworks, and tools to enhance our personalization and discovery systems.


• Mentor and guide a team of engineers, fostering a culture of technical excellence, innovation, and continuous learning.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or a related field (PhD preferred)


• 10+ years of experience in AI/ML engineering, with a proven track record of building and deploying large-scale, consumer facing personalization or recommendation systems.


• Experience developing LLM techniques—including post-training, evaluation, inference, and APIs.


• Sufficient business and technical acumen in using AI techniques like prompt engineering and RAG to solve challenging problems.


• Deep expertise in machine learning, deep learning, and data science, including hands-on experience with frameworks such as TensorFlow, PyTorch, and modern LLMs.


• Proficiency in Python and familiarity with production ML pipelines, cloud services (e.g., AWS, GCP), and data engineering best practices.


• Strong understanding of user engagement metrics and experience applying AI/ML to optimize user-facing products.


• Curiosity, adaptability, and a drive for continuous learning and innovation in the rapidly evolving AI landscape
  

Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.

The cash compensation range for this role is $250,000 - $325,000
 
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.