ML Engineering Manager (AI Products)

Location: San Francisco Bay Area

Perplexity is seeking a Machine Learning / Software Engineering Manager to lead the AI Products team to build our AI Products spanning from the Comet Browser Agent, to the Deep Research Search Agent to integrating our core search experience with frontier capabilities like MCP as well as integrating different vertical end-to-end experiences like Travel, Shopping, Finance.

Responsibilities

• Provide engineering leadership across multiple layers of rapidly growing products in the agents space.
• Leverage your experience in post-training deep foundational models with prompting to provide the best Research agent experience for both the Perplexity core search as well as the Browser.
• Drive product reliability, code quality, testing, and maintenance for the broader team.
• Oversee hiring, onboarding and ensure strong research and engineering practices for a rapidly growing team. Develop rigorous interview pipelines and work closely with recruiting to source candidates.
• Collaborate closely with the Core Research / Post-Training, Inference and Search teams.
• Interface with the Perplexity co-founders to deliver a top priority strategic objective for the company and industry.

Qualifications

• Strong foundational familiarity with Deep Learning, Agents Products, Evals, as well as the open source training stack.
• Have a strong product intuition and taste for user experience excellence.
• Ability to make hard technical and research tradeoffs as well as remove research and engineering blockers.
• Strong organizational skills for managing and delivering parallel technical projects.
• Experience managing medium size teams of engineers.
• Experience leveraging the right combination of open source and in-house solutions.
• 9+ years of general engineering experience.
• 3+ years of ML / deep learning experience.
• 5+ years of engineering management experience.

Nice to Have

• Familiarity with SFT, Preference Optimization algorithms, Reinforcement Learning
• Fair understanding of statistics, probability, evaluations, and A/B testing.