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Machine Learning Engineer Intern (FeatureStore) - 2025 Summer (PhD)

Machine Learning Engineer Intern (FeatureStore) - 2025 Summer (PhD)

Tik TokSan Jose, CA, United States
Hace 1 día
Tipo de contrato
  • A tiempo completo
Descripción del trabajo

Responsibilities

Team Introduction : The TikTok Data Ecosystem Team plays a critical role in supporting TikTok's personalized recommendation system, which serves over 1 billion users. We are responsible for building scalable, reliable, and high-performance infrastructure for storing and serving machine learning features - especially user behavior sequences and contextual embeddings used in large-scale recommendation and pretraining models. Our work sits at the intersection of systems and machine learning : ensuring training-serving consistency, low-latency access to temporal features, and scalable ingestion pipelines across online and offline environments. We explore and integrate with various underlying storage engines, including RocksDB, HBase, and time-series databases, depending on the access pattern, feature type, and serving latency required by ML models. Responsibilities : - Build and optimize the core infrastructure of TikTok's feature store, powering both training data pipelines and real-time inference systems. - Design efficient storage strategies for user behavior sequences, long-range contextual features, and sparse embeddings - ensuring freshness, consistency, and high availability. - Work with underlying storage engines such as RocksDB, HBase, and time-series databases to support feature retention, versioning, compaction, and fast lookup. - Collaborate with recommendation algorithm teams to design schemas and access patterns tailored to evolving model needs. - Integrate online and offline data pipelines to reduce training-serving skew and support continuous training and A / B testing scenarios. - Investigate techniques such as temporal sampling, embedding quantization, caching, and hybrid tiered storage to improve cost-efficiency and latency.

Qualifications

Minimum Qualifications : - Currently pursuing a PhD's degree or above in Computer Science, Software Engineering, or a related technical field. - Solid foundation in distributed systems, data storage, and stream / batch processing architectures. - Experience in programming with Java, C++, or Python. - Understanding of key-value stores, LSM-tree architectures, or time-series databases at a system level. - Eagerness to work on ambiguous, real-world infrastructure problems that impact ML product outcomes. Preferred Qualifications : - Graduating in December 2025 or later with intent to return to your program. - Experience working with RocksDB, HBase, or time-series storage engines like IoTDB, OpenTSDB, or custom LSM-tree variants. - Familiarity with feature store design, feature lifecycle management, and streaming ingestion pipelines. - Understanding of recommendation system workflows, such as two-tower models, real-time CTR prediction, or user intent modeling. - Contributions to open-source storage / ML infra projects or participation in ML system hackathons.

Job Information

[For Pay Transparency]Compensation Description (Hourly) - Campus Intern

The hourly rate range for this position in the selected city is $60- $60.

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.

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.

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.

We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

TikTok Accommodation

TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at

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Machine Learning Engineer • San Jose, CA, United States

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