Machine Learning Engineer, Search Ads - USDS
About the position
TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. U.S. Data Security (USDS) is a subsidiary of TikTok in the U.S., created to enhance focus and governance on our data protection policies and content assurance protocols to ensure the safety of U.S. users. Our commitment is to provide oversight and protection of the TikTok platform and U.S. user data, allowing millions of Americans to continue using TikTok for learning, earning, creative expression, and entertainment. The teams within USDS that deliver on this commitment include Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions, and more. The Search Ads team is at the forefront of monetization strategies across our apps, including TikTok, TopBuzz, and BuzzVideo. This team is dedicated to building a globally leading Search Ads monetization system. As a Machine Learning Engineer on this team, you will have the opportunity to work on large-scale distributed storage and architecture, as well as tackle complex problems related to Natural Language Processing (NLP), ranking, and information retrieval. You will play a crucial role in innovating and optimizing our ad formats, creative displays, and the return on investment (ROI) of ad delivery. We are looking for candidates who are passionate about overcoming challenges and developing our Search Ads product from the ground up alongside a world-class team of engineers. To foster collaboration and cross-functional partnerships, our organization currently follows a hybrid work schedule, requiring employees to work in the office three days a week, or as directed by their manager. This model is regularly reviewed, and specific requirements may change at any time.
Responsibilities
Participate in the development of a large-scale Ads system
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Responsible for relevance model and strategy optimization, such as semantic matching models, text/photo/video multi-model, ranking strategy, etc
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Participate in the development and iteration of Ads algorithms using Machine Learning
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Work on NLP (Natural Language Processing) capability improvement and query understanding, such as query classification, seq2seq, NER (Named Entity Recognition), knowledge graph, bidword optimization, etc
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Work on CTR/CVR model estimation accuracy, data analysis, modeling, feature engineering
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Research and develop Ads pacing algorithms, ads traffic control, etc
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Partner with product managers and product strategy & operation team to define product strategy and features
Requirements
BS degree in Computer Science, Computer Engineering or other relevant majors
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Excellent programming, debugging, and optimization skills in general purpose programming languages
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Ability to think critically and to formulate solutions to problems in a clear and concise way.
Nice-to-haves
Experience with one or more general purpose programming languages including but not limited to: Go, C/C++, Python
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Good understanding in one of the following domains: ad fraud detection, risk control, quality control, adversarial engineering, and online advertising systems
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Good knowledge in one of the following areas: machine learning, deep learning, backend, large-scale systems, data science, full-stack.
Benefits
100% premium coverage for employee medical insurance
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Approximately 75% premium coverage for dependents
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Health Savings Account (HSA) with a company match
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Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans
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Flexible Spending Account (FSA) Options like Health Care, Limited Purpose and Dependent Care
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10 paid holidays per year
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17 days of Paid Personal Time Off (PPTO)
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10 paid sick days per year
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12 weeks of paid Parental leave
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8 weeks of paid Supplemental Disability
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Mental and emotional health benefits through EAP and Lyra
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401K company match
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Gym and cellphone service reimbursements
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