Data Lake & ML Analytics Engineer

Pangle; San Jose, Northern (CA, KY); Hybrid; USD 140,000 - 210,000; Full time

Job summary

ByteDance’s Applied Machine Learning Ark team in San Jose develops and operates Large Language Model (LLM) service platforms, delivering MaaS solutions for both providers and downstream users. We’re building end-to-end systems spanning LLM training, fine-tuning, inference, prompt engineering, and intelligent agent frameworks.

Join us to design data lakes, large-scale pipelines, and analytics platforms that derive quality signals from vast logs to inform model improvement and product decisions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field.
• Solid fundamentals in data structures, algorithms, and distributed systems.
• Strong programming skills in at least one mainstream language, plus proficiency in SQL.
• Hands-on experience with a big data engine or lakehouse storage system.
• Demonstrated ability through substantial projects, internships, research, or open-source work.

Responsibilities

• Build and maintain the data lake that powers model and agent development, including storage design, query performance, and cost efficiency.
• Develop large-scale batch and streaming pipelines that turn raw model and agent logs into analysis-ready datasets.
• Build analytics and metrics platforms that let algorithm and product teams find actionable insights quickly.
• Own data quality and governance, and partner with algorithm teams to support the data flywheel behind continuously improving systems.

Skills

Bachelor's degree

Data structures

Algorithms

Distributed systems

SQL

Programming language

Education

Bachelor's or Master's in CS/SE/DS

Tools

Big data engine

Lakehouse storage

Job description

ByteDance’s Applied Machine Learning Ark team in San Jose develops and operates Large Language Model (LLM) service platforms, delivering MaaS solutions for both providers and downstream users. We’re building end-to-end systems spanning LLM training, fine-tuning, inference, prompt engineering, and intelligent agent frameworks.

Join us to design data lakes, large-scale pipelines, and analytics platforms that derive quality signals from vast logs to inform model improvement and product decisions.