5+ years of experience in ML/AI model development for user-facing products
Deep expertise in deep learning frameworks (PyTorch, TensorFlow, JAX)
Strong software engineering skills with an emphasis on Python
In-depth understanding of the full ML lifecycle from data analysis to model monitoring
Proven communication and collaboration skills in cross-functional teams
Curiosity and passion for enhancing user impact through ML/AI
Degree in Computer Science, Engineering, or related field (or equivalent experience)
Responsibilities
Apply advanced ML and LLM techniques to enhance personalization, query understanding, and content discovery
Evaluate ML models using offline and online methods, creating metrics for insight into performance
Manage the entire model lifecycle from research to production, including testing and iterative improvements
Work collaboratively with engineers, PMs, and designers to integrate AI into product development
Stay updated on ML/AI trends and incorporate new research into model enhancements
Benefits
Opportunities for professional growth and learning in cutting-edge technologies
Collaborative and innovative team environment
Impactful work influencing a global user base
Exposure to the latest ML/AI research and applications
Flexible working environment and possible remote options
Full Job Description
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).
