Research Engineer: Data Lake Infra & Analytics (Graduate)

ByteDance; Seattle (WA); On-site; USD 150,000 - 210,000; Full time

Job summary

ByteDance in Seattle is seeking engineers and researchers to join the Applied Machine Learning Ark, building MaaS platforms and end-to-end LLM solutions for text and multimodal models. You will design and operate data lakes, batch and streaming pipelines, and analytics platforms, while ensuring data quality and governance to inform model improvement and product decisions at scale.

This is a collaborative, data-driven role with opportunities to contribute to research and shape engineering

Qualifications

• PhD required or completed in CS/related field.
• Strong fundamentals in data structures, algorithms and distributed systems.
• Proficiency in at least one mainstream programming language and SQL.
• Hands-on experience with big data engine or lakehouse storage.

Responsibilities

• Build and maintain the data lake powering model and agent development.
• Develop large-scale batch and streaming pipelines from logs to analysis-ready datasets.
• Build analytics and metrics platforms for rapid insights.
• Own data quality and governance to support data-driven improvements.

Skills

PhD in Computer Science/related field

Data structures & algorithms

Distributed systems

Programming + SQL

Big data lakehouse experience

Projects/Internships/Open-source work

Query engine & lakehouse internals

Streaming pipelines / OLAP

LLM/agent log analysis

Cloud-native infra & performance

Education

PhD in Computer Science/Software Engineering/Data Science or related field

Job description

ByteDance in Seattle is seeking engineers and researchers to join the Applied Machine Learning Ark, building MaaS platforms and end-to-end LLM solutions for text and multimodal models. You will design and operate data lakes, batch and streaming pipelines, and analytics platforms, while ensuring data quality and governance to inform model improvement and product decisions at scale.

This is a collaborative, data-driven role with opportunities to contribute to research and shape engineering