Principal Real-Time Recommendation Platform Engineer

ByLabs; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

ByLabs is seeking a Principal Recommendation Platform Engineer in San Francisco to evolve our real-time personalization platform from rule-based to ML-powered, leading architecture and end-to-end delivery for a high-throughput system serving tens of millions of users globally.

You will own feature pipelines, a unified Feature Store, and integrations with AI agents/LLMs, driving reliability, latency, and throughput while delivering measurable business impact.

Qualifications

• 4+ years of recommender systems engineering experience at a consumer internet company.
• Proficiency in Go, Java, or C++ with clean, scalable code.
• Experience building a real-time recommendation system serving tens of millions of users.

Responsibilities

• Develop high-throughput, low-latency recommendation services and improve performance and reliability.
• Build stream-and-batch feature pipelines and a Feature Store for online/offline features.
• Identify architectural needs across scenarios and optimize workflows.
• Develop core components and drive adoption of emerging technologies including LLMs and AI agents.

Skills

Go

Java

C++

Tools

Vector databases

Key-value stores

Big-data systems

Job description

ByLabs is seeking a Principal Recommendation Platform Engineer in San Francisco to evolve our real-time personalization platform from rule-based to ML-powered, leading architecture and end-to-end delivery for a high-throughput system serving tens of millions of users globally.

You will own feature pipelines, a unified Feature Store, and integrations with AI agents/LLMs, driving reliability, latency, and throughput while delivering measurable business impact.