Senior Machine Learning Engineer (Multiple Positions)

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.

About the Team

Our team plays a crucial role in ensuring the company’s success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you’ll be part of a team that’s developing new solutions to new challenges. It’s working fast, at scale, and we’re making a difference. We are looking for talents to join us on this exciting journey!

Responsibilities

Work across the full machine learning (ML) modeling lifecycle, including data preparation, feature engineering, hyperparameter tuning and evaluation, and model selection to develop, build, and optimize the performance of large and highly scalable ML systems, algorithms, strategies, models and/or infrastructures. Formulate real-world user data modeling in statistical learning problems. Design and execute user procedure experiments, tests, and significance analyses by applying statistical test theories to optimize user experience. Build and train ML models, deep learning models and their variants to analyze and predict user behavior metrics and treatment effects with ML frameworks. Use big data frameworks and analytics tools to aggregate, collate, and analyze data. Research and design ML models to optimize systems, features, algorithms, and product strategies. Collaborate with key stakeholders and cross-functional teams to define product strategy and features, and to assist in defining products and driving initiatives from a ML engineering viewpoint. Mentor junior Machine Learning Engineers and interns.