Member of Technical Staff (Software Engineer, Applied AI)
At a glance
Senior AI Engineering role at Perplexity. San Francisco · full-time · $220,000–$405,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Use machine learning and LLM methods for personalization, including memory, context summaries, retrieval, ranking and recommendations
- Extend Perplexity Computer with new agent capabilities and build an autonomous harness for its agent squad to explore problems
- Create research tools and experiments for offline and online testing, with metrics that reveal quality and impact
- Take models from data analysis through deployment, evaluation, A/B tests and continued improvement
- Work with engineering, product, data science and design peers, bringing useful research and algorithms into the product
What you bring
- At least five years building and shipping AI products for large-scale user-facing or data-driven applications
- Strong Python and software engineering skills, including production code and collaborative development
- Hands-on command of the AI lifecycle, from data analysis and evaluation to monitoring and iteration
- A computer science, engineering or related degree at the bachelor's level or higher, or equivalent experience
Who this fits
This senior role suits an applied AI engineer who enjoys product-focused work and collaborating across engineering, product, data science and design. The position is based in San Francisco.
From the employer
Perplexity is looking for an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering our core experience in Perplexity Computer. Working in this mission critical team, you will develop frontier context layer applications - fulfilling the curiosity of millions of users across the globe.
Key Responsibilities
Apply state-of-the-art ML and LLM techniques to solve problems spanning:
Personalization (LLM memory, context summarization, retrieval and ranking);
Contextual recommendations and Monetization applications
Build frontier agent capabilities on top of Perplexity Computer
Build auto research harness for both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact.
Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement and build autonomous harness for agent squad to explore different problem spaces.
Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements.
Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle.
Preferred Qualifications
5+ years experience building and shipping robust AI products for large-scale, user-facing or data-driven products.
Strong software engineering skills (Python, production-quality codebases, collaborative development) and experience using agentic coding tools for large scale parallel developments.
In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, and ongoing monitoring/improvement.
Proven collaborator and communicator; excels in high-velocity, cross-functional teams.
Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI.
BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience).
Bonus Points For
Experience with LLM context engineering or harness engineering.
Experience in mid-training or post-training frontier open source models
Experience in large scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking, etc).