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Machine Learning Engineer, Recommendation - E-CommerceTik Tok • United States
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Machine Learning Engineer, Recommendation - E-Commerce

Tik Tok
  • US
    United States
  • US
    United States
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Über

Machine Learning Engineer, Recommendation - E-Commerce
Location: San Jose Employment Type: Regular Job Code: A256265A Responsibilities
About the Teams E-commerce - Recommendation and Marketing E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. We are a group of applied machine learning engineers and research scientists that focus on E-commerce recommendations. We are responsible for building up and scaling our recommendation system to provide the most stable and best shopping experience for our TikTok users. E-commerce - Alliance The 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. E-commerce - Search The Search E-Commerce team is responsible for the search algorithm for TikTok's rapidly growing global e-commerce business. We use state-of-the-art large-scale machine learning technology, the cutting-edge NLP, CV and multi-modal technology to build the industry's top-class search engine to provide the best e-commerce search experience, for more than 1 billion monthly active TikTok users around the world. E-commerce - Search Growth The Search Growth E-commerce team is at the forefront of developing the search recommendation algorithm for TikTok's rapidly expanding global e-commerce enterprise. Utilizing cutting-edge machine learning technology, advanced NLP, CV, recommendation, and multi-modal technology, we're shaping a pioneering engine within the industry. Our objective is to deliver the ultimate e-commerce search experience to over 1 billion active TikTok users worldwide. Our mission: to create a world where "there are no hard-to-sell, overpriced products." What You Will Do Responsible for the build and design of optimization algorithm strategies for large-scale (10 million to 100 million products or creators' contents) e-commerce recommendation algorithm pipeline Build long and short term user interest models, analyze 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. Qualifications
Minimum Qualifications Bachelor above degree in computer science or relevant areas. 3+ years of experience with a solid foundation in data structure and algorithm design, and be proficient in using one of the programming languages such as Python, Java, C++, R, etc.; Familiar with common machine/deep learning, causal inference, and operational optimization algorithms, including classification, regression, clustering methods, as well as mathematical programming and heuristic algorithms; Familiar with at least one framework of TensorFlow / PyTorch / MXNet and its training and deployment details,as well as the training acceleration methods such as mixed precision training and distributed training; Familiar with big data related frameworks and application, those who are familiar with MR or Spark are preferred Preferred Qualifications: Experience in recommendation systems, online advertising, ranking, search, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields. Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc. Job Information
For Pay TransparencyCompensation Description (Annually) The base salary range for this position in the selected city is $150000 - $316800 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. For Los Angeles County (unincorporated) Candidates: 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: 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. 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. Diversity & Inclusion
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. TikTok Accommodation
TikTok 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 https://tinyurl.com/RA-request
  • United States

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