Principal ML Engineer, Real-Time Recommendation Platform

ByLabs; Seattle (WA); On-site; USD 180,000 - 280,000; Full time

Job summary

ByLabs is hiring a Principal Recommendation System/Platform Engineer in Seattle to lead upgrading our core architecture and ML platform. You will drive transformation from rule-based personalization to an industrial-scale, real-time system serving millions of users.

You will collaborate across algorithm, growth, and data science teams to deliver high-throughput, low-latency services, training pipelines, and production-ready deployment with robust observability and disaster recovery.

Qualifications

• 4+ years in recommender systems engineering at consumer internet scale.
• Experience building model training and deployment platforms.
• Hands-on with Go, Java, or C++ and modern ML frameworks.

Responsibilities

• Develop high-throughput, low-latency recommendation services and reliability mechanisms.
• Build scalable model training infrastructure with distributed training and scheduling.
• Create deployment and online inference capabilities with autoscaling and canary releases.
• Monitor model quality and system performance; implement alerting for incidents.
• Collaborate with algorithm and engineering teams to standardize training and inference flows.

Skills

Recommender systems

Distributed training

Go/Java/C++

Tools

PyTorch

TensorFlow

Job description

ByLabs is hiring a Principal Recommendation System/Platform Engineer in Seattle to lead upgrading our core architecture and ML platform. You will drive transformation from rule-based personalization to an industrial-scale, real-time system serving millions of users.

You will collaborate across algorithm, growth, and data science teams to deliver high-throughput, low-latency services, training pipelines, and production-ready deployment with robust observability and disaster recovery.