Applied AI Engineer: Frontier Agents & Personalization

Fdetimes

San Francisco (CA)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

Perplexity is seeking an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering our Perplexity Computer experience in San Francisco. You will own the model lifecycle from research to production, including data analysis, evaluation, offline/online testing, and continuous improvement, collaborating with engineers, PMs, data scientists, and designers.

Strong Python software engineering skills and a track record shipping AI products at scale are essential, with a passion

Qualifications

  • 5+ years of experience building and shipping robust AI products.
  • Strong software engineering skills in Python and production-quality codebases.
  • Experience across the full AI lifecycle: data analysis, evaluation, and monitoring.
  • Proven collaborator in high-velocity, cross-functional teams.
  • Curious and driven by end-user/product impact and advancing applied ML/AI.
  • BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent).

Responsibilities

  • Apply state-of-the-art ML and LLM techniques to personalize experiences and solve problems.
  • Develop frontier context layer applications on top of Perplexity Computer.
  • Own the entire model lifecycle from research to production, including A/B testing.
  • Collaborate with engineers, PMs, data scientists, and designers to drive product improvements.
  • Stay at the forefront by evaluating and incorporating emerging research and algorithms.

Skills

AI product development
Python programming
Cross-functional collaboration
End-to-end AI lifecycle
User impact
Advanced ML techniques

Education

BS/MS/PhD in Computer Science or related field

Tools

Python

Job description

Perplexity is seeking an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering our Perplexity Computer experience in San Francisco. You will own the model lifecycle from research to production, including data analysis, evaluation, offline/online testing, and continuous improvement, collaborating with engineers, PMs, data scientists, and designers.

Strong Python software engineering skills and a track record shipping AI products at scale are essential, with a passion

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