TikTok
Machine Learning Engineer / Applied Scientist, Recommendations, E-Commerce Allia
TikTok, Seattle, Washington, us, 98127
Responsibilities
TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. U.S. Data Security (“USDS”) is a subsidiary of TikTok in the U.S. This new, security-first division was created to bring heightened focus and governance to our data protection policies and content assurance protocols to keep U.S. users safe. Our focus is on providing oversight and protection of the TikTok platform and U.S. user data, so millions of Americans can continue turning to TikTok to learn something new, earn a living, express themselves creatively, or be entertained. The teams within USDS that deliver on this commitment daily span across Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions, and more.
Why Join UsCreation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible. Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day. To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve. Join us.
About the teamThe e-commerce alliance team aims to serve merchants and creators in the e-commerce platform to meet merchants' business indicators and improve creators' creative efficiency. By cooperating with merchants and creators, we aim to provide high-quality content and a personalized shopping experience for TikTok users, create efficient shopping tools at seller centers, and promote cooperation between merchants and creators.
We are actively seeking an
Applied Scientist
to join our Global E-Commerce Alliance Team. This role is centered on developing and implementing innovative machine learning solutions for our recommendation systems in E-Commerce business. The successful candidate will work closely with cross-functional teams, providing expert insight and influencing critical decision-making across multiple areas of our business.
Responsibilities:Collaborate with cross-functional teams to design, develop, and deploy sophisticated machine learning algorithms to enhance the performance of our recommendation systems.Utilize the ML, NLP, and CV techniques to deal with real-world signals generated from products, creators, merchants, e-commerce transactions, and so on.Design and deploy the large recommendation model, in the online learning manner, to serve billions of queries and products.Formulate end-to-end machine learning models for recommendation systems, ensuring their efficient and effective operation.Analyze extensive, complex datasets to extract meaningful insights, identify opportunities for improvement, and facilitate data-driven decision-making.Design and execute experiments, testing and iterating on machine learning models to optimize recommendation functions and boost user satisfaction.Stay abreast of the latest advances in machine learning and recommendation systems, integrating this knowledge into your work.Clearly communicate complex technical concepts, methodologies, and results to a diverse audience, influencing decisions based on your findings.Adhere to stringent data governance and privacy protocols, ensuring all user data is handled responsibly and ethically.
QualificationsPhD or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline.Solid experience in machine learning, deep learning, data mining, or artificial intelligence.Proficient in programming languages such as Python, C++, Java, or similar.Deep understanding of recommendation algorithms and personalization systems.Excellent problem-solving and analytical skills.Strong ability to communicate complex ideas effectively to both technical and non-technical audiences.
Preferred Skills:Experience with reinforcement learning techniques.Proven modeling/algorithms competition records on Kaggle or top conferences’ challenges.Proven programming competition records on ICPC, IOI or USACO.Experience working with recommendation systems, computational advertising, search engine, E-commerce recommendation systems.Publications in machine learning or related conferences or journals are highly desirable.
Job Information:Compensation Description (annually)The base salary range for this position in the selected city is $137750 - $237500 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.Our company benefits are designed to convey company culture and values, to create an efficient and inspiring work environment, and to support our employees to give their best in both work and life. We offer the following benefits to eligible employees:We cover 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents and offer a Health Savings Account(HSA) with a company match. As well as Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans. In addition to Flexible Spending Account(FSA) Options like Health Care, Limited Purpose and Dependent Care.Our time off and leave plans are: 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) and 10 paid sick days per year as well as 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.We also provide generous benefits like mental and emotional health benefits through our EAP and Lyra. A 401K company match, gym and cellphone service reimbursements. The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
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TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. U.S. Data Security (“USDS”) is a subsidiary of TikTok in the U.S. This new, security-first division was created to bring heightened focus and governance to our data protection policies and content assurance protocols to keep U.S. users safe. Our focus is on providing oversight and protection of the TikTok platform and U.S. user data, so millions of Americans can continue turning to TikTok to learn something new, earn a living, express themselves creatively, or be entertained. The teams within USDS that deliver on this commitment daily span across Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions, and more.
Why Join UsCreation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible. Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day. To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve. Join us.
About the teamThe e-commerce alliance team aims to serve merchants and creators in the e-commerce platform to meet merchants' business indicators and improve creators' creative efficiency. By cooperating with merchants and creators, we aim to provide high-quality content and a personalized shopping experience for TikTok users, create efficient shopping tools at seller centers, and promote cooperation between merchants and creators.
We are actively seeking an
Applied Scientist
to join our Global E-Commerce Alliance Team. This role is centered on developing and implementing innovative machine learning solutions for our recommendation systems in E-Commerce business. The successful candidate will work closely with cross-functional teams, providing expert insight and influencing critical decision-making across multiple areas of our business.
Responsibilities:Collaborate with cross-functional teams to design, develop, and deploy sophisticated machine learning algorithms to enhance the performance of our recommendation systems.Utilize the ML, NLP, and CV techniques to deal with real-world signals generated from products, creators, merchants, e-commerce transactions, and so on.Design and deploy the large recommendation model, in the online learning manner, to serve billions of queries and products.Formulate end-to-end machine learning models for recommendation systems, ensuring their efficient and effective operation.Analyze extensive, complex datasets to extract meaningful insights, identify opportunities for improvement, and facilitate data-driven decision-making.Design and execute experiments, testing and iterating on machine learning models to optimize recommendation functions and boost user satisfaction.Stay abreast of the latest advances in machine learning and recommendation systems, integrating this knowledge into your work.Clearly communicate complex technical concepts, methodologies, and results to a diverse audience, influencing decisions based on your findings.Adhere to stringent data governance and privacy protocols, ensuring all user data is handled responsibly and ethically.
QualificationsPhD or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline.Solid experience in machine learning, deep learning, data mining, or artificial intelligence.Proficient in programming languages such as Python, C++, Java, or similar.Deep understanding of recommendation algorithms and personalization systems.Excellent problem-solving and analytical skills.Strong ability to communicate complex ideas effectively to both technical and non-technical audiences.
Preferred Skills:Experience with reinforcement learning techniques.Proven modeling/algorithms competition records on Kaggle or top conferences’ challenges.Proven programming competition records on ICPC, IOI or USACO.Experience working with recommendation systems, computational advertising, search engine, E-commerce recommendation systems.Publications in machine learning or related conferences or journals are highly desirable.
Job Information:Compensation Description (annually)The base salary range for this position in the selected city is $137750 - $237500 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.Our company benefits are designed to convey company culture and values, to create an efficient and inspiring work environment, and to support our employees to give their best in both work and life. We offer the following benefits to eligible employees:We cover 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents and offer a Health Savings Account(HSA) with a company match. As well as Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans. In addition to Flexible Spending Account(FSA) Options like Health Care, Limited Purpose and Dependent Care.Our time off and leave plans are: 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) and 10 paid sick days per year as well as 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.We also provide generous benefits like mental and emotional health benefits through our EAP and Lyra. A 401K company match, gym and cellphone service reimbursements. The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
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