Machine Learning Engineer, Recommendations- USDS Responsibilities

We are a group of applied machine learning engineers and data scientists focusing on general feed recommendations and E-commerce recommendations. We develop innovative algorithms and techniques to improve user engagement and satisfaction, converting ideas into business-impacting solutions.

Participate in building large-scale (10 million to 100 million) recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations, etc., as used in platforms like TikTok.

Build long and short term user interest models, analyze and extract relevant information from large data, and design algorithms to explore users' latent interests efficiently.

Design, develop, evaluate and iterate on predictive models for candidate generation and ranking (e.g., Click Through Rate and Conversion Rate prediction), including real-time data pipelines, feature engineering, model optimization and innovation.

Design and build supporting/debugging tools as needed.

In order to enhance collaboration and cross-functional partnerships, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. The hybrid model is regularly reviewed and requirements may change.

Qualifications

Minimum Qualifications

Bachelor's degree or higher in Computer Science or related fields.

Strong programming and problem-solving ability.

Experience in applied machine learning, familiar with one or more algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep, etc.

Experience in Deep Learning Tools such as TensorFlow/PyTorch.

Experience with at least one programming language like C++/Python or equivalent.

Preferred Qualifications

Experience in recommendation systems, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.

Publications at KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS or experience in data mining/machine learning competitions (e.g., Kaggle).

About USDS

TikTok is the leading destination for short-form mobile video. U.S. Data Security (USDS) is a TikTok subsidiary in the U.S. focused on data protection policies and content assurance to keep U.S. users safe. Our teams span Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions and more.

Data Security Statement

This role requires the ability to work with and support systems designed to protect sensitive data. The role is subject to strict national security-related screening.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product helps people express themselves, discover, connect, and be entertained. We value curiosity, humility, and impact, and work as one team to achieve meaningful breakthroughs.

Diversity & Inclusion

TikTok is committed to an inclusive space where employees are valued for their skills, experiences, and perspectives. We celebrate diverse voices and aim to reflect the communities we reach.

USDS Reasonable Accommodation

USDS provides reasonable accommodations in recruitment processes for candidates with disabilities or other protected reasons. If you need assistance, please reach out at https://tinyurl.com/USDS-RA.

Job Information

Compensation: The base salary range for this position is $177,688 - $341,734 annually. Total compensation may include bonuses, incentives, and stock units. Benefits vary by location and role. Paid holidays, paid time off, and health benefits are provided on day one where applicable. The company reserves the right to modify benefits at any time.

Note: This posting may include location-based salary data for reference. Actual offers are determined by factors including qualifications, skills, and location.

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