Research Engineer, Data Lake Infrastructure & Data Analytics Graduate (AML-Ark-US) - 2027 Start (PhD)

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of products including TikTok, Lemon8, CapCut, Pico, Toutiao, Douyin, and Xigua, ByteDance makes it easier and more fun for people to connect with, consume, and create content. The Applied Machine Learning Ark team combines system engineering and machine learning to develop and operate Large Language Model (LLM) service platforms offering Model-as-a-Service (MaaS) solutions for businesses, serving both large model providers and downstream users. The US team drives the design, development, and operation of MaaS solutions across the US and international markets outside mainland China, building full-stack, end-to-end solutions spanning text and multimodal LLM algorithms, training/fine-tuning/inference frameworks, prompt engineering, model alignment, and intelligent agent systems.

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.
• Operate large-scale log analytics pipelines processing massive volumes of invocation logs from text models, multimodal models, and agent systems to extract usage patterns, quality signals, and actionable insights for model improvement, system optimization, and product decisions.

Qualifications

Minimum Qualifications:

• Individuals who are completing or have recently completed a PhD 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.

Preferred Qualifications:

• Understanding of query engine and lakehouse internals, including columnar storage and query optimization.
• Experience with streaming pipelines or OLAP systems.
• Experience analyzing LLM or agent logs and traces.
• Experience with cloud-native infrastructure and performance tuning at scale.

Successful candidates must be able to commit to an onboarding date by the end of the year.

Pay

The base salary range for this position is $153,900 - $300,960 annually. Compensation may vary depending on a candidate’s qualifications, skills, competencies, experience, and location. Base pay is one part of the total package, which may also include discretionary bonuses/incentives and restricted stock units.

Benefits

• Day one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave.
• Short-term and long-term disability coverage.
• Life insurance.
• Wellbeing benefits.
• 10 paid holidays per year.
• 10 paid sick days per year.
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).