Machine Learning Engineer Intern (TikTok-Local Services-LBS Platform) - 2026 Start (PhD)

Responsibilities

TikTok Location Based Service Team's goal is to deliver user-facing products based on the location that connects people with places, localized content, and service in the real world around the globe. We leverage POI data, geolocation, and large-scale location-based services (LBS) technologies to provide comprehensive LBS product and service capabilities for overseas businesses.

We are looking for talented individuals to join us for an internship in 2026. Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at TikTok.

PhD internships at TikTok provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts.
Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).

Responsibilities:
Work on ML models and algorithms to drive the creation of cutting-edge technical solutions to bridge the gap between technical capabilities and real-world business impact, including POI data production, POI recommendation, reviews sentiment analysis and ranking, geocoding, user profiling, etc.
-Responsible for algorithmic strategies in geographical content and services, enhancing and optimizing Location-Based Services (LBS) capabilities to support a range of international products.
-Thoroughly comprehend business intricacies, analyze issues, and devise appropriate algorithms and strategies tailored to various problem domains. Continuously optimize performance and efficacy.

Qualifications

Minimum Qualifications:
- Currently pursuing a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline;
-Experienced in programming and algorithmic skills, proficient in languages such as Python, Golang, or C++.
-Deep understanding of computer architectures, data structures and algorithms.
-Experienced in one or more of the following topics: Tensorflow, Caffe, MxNet, PyTorch or other machine learning frameworks
-Have good team communication and collaboration skills.

Preferred Qualifications:
- Graduating December 2026 onwards with the intent to return to degree program after the completion of the internship.
-Experience or domain expertise in one or more of the following areas is preferred: POI (Point of Interest) data algorithms, NLP, recommendation systems, reviews sentiment analysis and ranking, NER, text mining, geocoding, user profiling, etc.
-Experience in big data, data warehouse, streaming data flow and real time data processing system is preferred.

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