Senior Machine Learning Engineer, Recommendations - USDS

Responsibilities

About the Team We are a group of applied machine learning engineers and data scientists that focus on general feed recommendations and E‑commerce recommendations. We are developing innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business‑impacting solutions. We are interested and excited in applying large‑scale machine learning to solve various real‑world problems.

What you will do:

• Participate in building large-scale (10 million to 100 million) recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in Tik Tok.
• Build long and short term user interest models, analyse and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
• Design, develop, evaluate and iterate on predictive models for candidate generation and ranking (eg. Click Through Rate and Conversion Rate prediction), including, but not limited to building real‑time data pipelines, feature engineering, model optimization and innovation.
• Design and build supporting/debugging tools as needed.

• 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 of the 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 Tensor Flow/PyTorch.
• Experience with at least one programming language like C++/Python or equivalent.

• Experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, large‑scale data mining, or related fields.
• Publications at KDD, NeurIPS,(Use the "Apply for this Job" box below). SIGIR, WSDM, ICML, IJCAI, AAAI, Rec Sys and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD‑cup etc.

USDS 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

Compensation Description (Annually):
The base salary range for this position in the selected city is $187,040 - $359,720 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short‑term and long‑term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

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.