This role pays more than
99%
of similar roles. Most pay
$174,600–$222,000
— the shaded band above.
At the midpoint, this role pays about
$346k
versus about
$198k
for comparable roles.
Based on 240 similar postings.
Employer
About Pinterest
Pinterest is a visual discovery and inspiration platform where people find ideas for home, style, recipes, and more. It serves hundreds of millions of users worldwide through its image and video pinboard product.
Pinterest currently has
82 open roles
on FindRole.
Listed pay typically runs
$164,695–$337,990
across 82 roles with salary data.
As a Principal Engineer, Core - Pinner Journeys, you will join the Core Engineering team to set the technical vision and lead foundational work across Homefeed, Search, and emerging AI Assistant experiences. You will define long-term architecture for retrieval, ranking, personalization, and generative features while driving a multi-year roadmap to unify signals and models. Your daily responsibilities include designing large-scale systems like multi-stage retrieval and representation learning, integrating LLMs into the core discovery stack, and establishing evaluation frameworks using causal inference. You will leverage expertise in search systems, multi-objective optimization, and generative AI technologies such as RAG and fine-tuning to solve complex discovery problems. This role requires deep technical leadership to improve relevance and monetization while mentoring senior engineers and ensuring high standards for reliability, performance, and safety across large-scale machine learning systems.
What does a Engineer earn in California?
Median $208000 from 94 postings across 22 companies.
Define long-term technical strategy and architecture for Homefeed, Search, and AI Assistant features.
Develop a multi-year roadmap to unify signals, features, and models across various discovery surfaces.
Design large-scale retrieval and ranking systems to improve relevance and monetization.
Architect the integration of LLMs and foundation models into the core discovery stack.
Establish technical frameworks for experimentation, measurement, and evaluation of generative use cases.
Provide hands-on leadership by designing critical components, reviewing code, and mentoring senior engineers.
Partner with product and data science teams to translate business goals into robust technical plans.
Improve engineering excellence regarding reliability, performance, security, and cost efficiency for ML systems.
What we're looking for
15+ years of industry experience in large-scale systems and/or machine learning with a track record in search, recommendations, feeds, or conversational AI.
Proven experience as a Principal Engineer, Architect, or equivalent senior technical leader driving cross-org strategy and execution.
Deep expertise in at least two areas: retrieval and ranking, representation learning, search systems, or LLMs and generative AI.
Demonstrated ability to define and drive multi-year architectural transformations at scale for core ranking stacks or feature platforms.
Strong product intuition and experience partnering with PM, Design, and Data Science on ambiguous products.
Exceptional communication skills to articulate strategy and technical direction to executives and broad engineering audiences.
Passion for mentoring senior/staff engineers and building engineering cultures.
Bachelor’s degree in computer science, a related field, or equivalent experience.
Prior experience in consumer discovery products at global scale (preferred).
Experience building or integrating AI assistants or agentic workflows into consumer experiences (preferred).
Distributed Systems
Java
Go
Rust
C/C++
Infrastructure as Code (IaC)
Cloud Infrastructure
Kernel Programming
System Programming
Data Plane
Telemetry
Fault Injection
rate‑limiting
Distributed Systems
Java
Go
Rust
C/C++
Linux
Kernel Programming
System Programming
Infrastructure as Code (IaC)
Cloud Infrastructure
Networking
Storage
Virtualization
Telemetry
Distributed Systems
Java
Go
Rust
C/C++
Linux
Kernel Programming
System Programming
Infrastructure as Code (IaC)
Cloud Infrastructure
Networking
Storage
Virtualization
Telemetry
Distributed Systems
Java
Go
Rust
C/C++
Linux
Kernel Programming
System Programming
Infrastructure as Code (IaC)
Cloud Infrastructure
Networking
Storage
Virtualization
Telemetry