Staff Machine Learning Engineer, TikTok BRIC Community Health
Actively Hiring
Full-time $254k - $480k Posted 2 days ago
Responsibilities
- check_circle Build machine learning solutions to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
- check_circle Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.
- check_circle Advance machine learning capabilities in areas such as risk perception and analysis, model interpretability, privacy and compliance, and adversarial robustness.
Basic qualifications
- Master's degree or above in Computer Science, Statistics, Machine Learning, or another relevant technical field, with at least 2 years of hands-on machine learning experience through industry, research, internships, or equivalent project work.
- Strong software engineering fundamentals and proficiency in Python or one of Java/C++/Go, with experience in large-scale data processing technologies such as Spark, Hadoop, or Hive.
- Strong machine learning fundamentals, with research or hands-on experience in areas such as deep learning, representation learning, graph learning, sequence/time-series modeling, transfer/multi-task learning, or unsupervised/self-supervised learning.
- Strong problem-solving and analytical skills, with the ability to reason and communicate in a result-oriented and data-driven manner.
- Natural curiosity and a strong passion for solving complex, ambiguous problems; willingness to dig deep, challenge assumptions, and continuously explore better solutions.
- Strong collaboration and communication skills, with the ability to work effectively across engineering, product, data, system and other cross-functional teams.
- Ability to work with a high degree of autonomy, learn quickly, and adapt to a rapidly evolving risk environment.
Preferred qualifications
- Industry experience in risk, fraud, spam, abuse detection, or related areas is preferred but not required.
- Experience building or deploying large-scale machine learning systems/algorithms is a plus.
- Hands-on experience with LLMs, generative AI, or agent development, including LLM-powered applications, evaluation pipelines, retrieval or knowledge systems, or agentic workflows.
- Research publications or strong research experience in relevant machine learning areas are a plus.
- Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
- Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
- Exercising sound judgment.
Tags & Focus Areas
Machine Learning Ai
About TikTok
Responsible for the NLP-related research and development, mainly including: Building the intent classifier in a full-stack manner by designing taxonomy, creating and managing high quality labeled data, training the best performed machine learning model (like Bert, GPT), and monitoring the online performance of the model. Building the prediction model by mapping the shopping journey of our users to chatbot actions, including suggesting common question-answers and transferring the user to hum...
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