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

ByteDance

$128K — $256K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's in Computer Science, Software Engineering, Data Science, or related field.
  • Strong foundation in data structures, algorithms, and distributed systems.
  • Proficiency in at least one mainstream programming language and SQL.
  • Experience with big data engines or lakehouse storage systems.
  • Practical experience demonstrated through projects, internships, or open-source contributions.

Responsibilities

  • Build and manage the data lake for model and agent development, focusing on storage design and cost efficiency.
  • Develop batch and streaming data pipelines to create analysis-ready datasets from raw logs.
  • Create analytics platforms for teams to quickly derive actionable insights from data.
  • Maintain data quality and governance, collaborating with algorithm teams for continuous system improvements.

Benefits

  • Day one access to medical, dental, and vision insurance.
  • 401(k) savings plan with company match.
  • Paid parental leave and disability coverage.
  • Life insurance and wellbeing benefits.
  • 10 paid holidays, 10 paid sick days, and 17 days of Paid Personal Time.
Full Job Description
Responsibilitie

The Applied Machine Learning Ark team combines system engineering and machine learning to develop and operate Large Language Model (LLM) service platforms that offer businesses Model-as-a-Service (MaaS) solutions, 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. We are building full-stack, end-to-end solutions spanning text and multimodal LLM algorithms, LLM training/fine-tuning/inference frameworks, prompt engineering, model alignment, and intelligent agent systems. Beyond model serving, we operate large-scale log analytics pipelines that process massive volumes of invocation logs from text models, multimodal models, and agent systems - extracting usage patterns, quality signals, and actionable insights to inform model improvement, system optimization, and product decisions through continuous, data-driven feedback loops. We are actively seeking talented engineers and researchers specializing in Large Language Models and AI Agent systems to join our dynamic team. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. 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.

Qualification

Minimum Qualifications: - Individuals who are completing or have recently completed a Bachelor's/ Master's 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.

Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $128000 - $256000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

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