Machine Learning Engineer Intern (Training Pre-processing) - 2025 Summer (PhD)

3+ months ago• San Jose, CA

About Us

Tik Tok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
Size: 5001-10000 employees

Industry: Entertainment & Gaming, Social Media, Technology

Responsibilities:

Team Introduction: The Tik Tok Flink Ecosystem Team plays a critical role in delivering real-time computing capabilities to power Tik Tok's massive-scale recommendation, search, and advertising systems. This team is focused on building the infrastructure for stream processing at exabyte scale - enabling ultra-low-latency, high-reliability, and cost-efficient real-time data transformations.

We are deeply involved in developing and optimizing Apache Flink and surrounding components like connectors, state backends, and runtime execution models to meet Tik Tok's rapidly evolving data needs at EB-level throughput and scale.

We also collaborate closely with ML infrastructure teams to bridge real-time stream processing and machine learning. This includes integrating Velox to accelerate model training, building multimodal data pipelines, and utilizing frameworks like Ray to orchestrate large-scale distributed ML workflows.

Responsibilities:

• Design and develop core Flink operators, connectors, or runtime modules to support Tik Tok's exabyte-scale real-time processing needs.
• Build and maintain low-latency, high-throughput streaming pipelines powering online learning, recommendation, and ranking systems.
• Collaborate with ML engineers to design end-to-end real-time ML pipelines, enabling efficient feature generation, training data streaming, and online inference.
• Leverage Velox for compute-optimized ML data transformation and training acceleration on multimodal datasets (e.g., video, audio, and text).
• Use Ray to coordinate distributed machine learning workflows and integrate real-time feature pipelines with ML model training/inference.
• Optimize Flink job performance, diagnose bottlenecks, and deliver scalable solutions across EB-scale streaming workloads.

Qualifications

Minimum Qualifications:

• Currently pursuing a PhD's degree in Computer Science, Software Engineering, Data Engineering, or a related technical field.
• Strong programming skills in Java, Scala, or Python.
• Understanding of distributed systems, stream processing, and event-driven architecture.
• Familiar with system design concepts such as fault tolerance, backpressure, and horizontal scalability.
• Demonstrated ability to debug and analyze complex distributed jobs in production environments.

Preferred Qualifications:

• Graduating in December 2025 or later, with the intent to return to your academic program.
• Experience with Apache Flink, Spark Streaming, or Kafka Streams.
• Hands-on experience with Ray for distributed ML or workflow orchestration.
• Familiarity with Velox, Arrow, or similar columnar execution engines for training/feature pipelines.
• Understanding of multimodal data processing (e.g., combining video, audio, and text in model training pipelines).
• Experience working with data lake ecosystems (e.g., Iceberg, Hudi, Delta Lake) and cloud-native storage at PB-EB scale.
• Contributions to open-source projects or participation in ML/engineering hackathons or competitions.

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Client-provided location(s): San Jose, CA

Job ID: Tik Tok-7498908264136165650

Employment Type: INTERN

Posted: 2025-05-02T00:32:28
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Perks and Benefits

Health and Wellness

• Health Insurance
• Dental Insurance
• Vision Insurance
• HSA
• Life Insurance
• Fitness Subsidies
• Short-Term Disability
• Long-Term Disability
• On-Site Gym
• Mental Health Benefits
• Virtual Fitness Classes

Parental Benefits

• Fertility Benefits
• Adoption Assistance Program
• Family Support Resources

Work Flexibility

• Flexible Work Hours
• Hybrid Work Opportunities

Office Life and Perks

• Casual Dress
• Snacks
• Pet-friendly Office
• Happy Hours
• Some Meals Provided
• Company Outings
• On-Site Cafeteria
• Holiday Events

Vacation and Time Off

• Paid Vacation
• Paid Holidays
• Personal/Sick Days
• Leave of Absence

Financial and Retirement

• 401(K) With Company Matching
• Performance Bonus
• Company Equity

Professional Development

• Promote From Within
• Access to Online Courses
• Leadership Training Program
• Associate or Rotational Training Program
• Mentor Program

Diversity and Inclusion

• Diversity, Equity, and Inclusion Program
• Employee Resource Groups (ERG)

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