{"schemaVersion":"jobsearcher.job.v1","id":"c0eb4828814bde7fd39c5b4b","url":"https://jobsearcher.com/jobs/c0eb4828814bde7fd39c5b4b","canonicalUrl":"https://jobsearcher.com/jobs/c0eb4828814bde7fd39c5b4b","title":"Machine Learning Engineer, Recommendation - E-Commerce","description":"Machine Learning Engineer, Recommendation - E-Commerce\r\nLocation: San Jose\r\nEmployment Type: Regular\r\nJob Code: A256265A\r\nResponsibilities\r\nResponsible for the build and design of optimization algorithm strategies for large-scale e-commerce recommendation algorithm pipeline.\r\nBuild long and short term user interest models, analyze and extract relevant information from large amounts of data and design algorithms to explore users' latent interests efficiently.\r\nDesign, develop, evaluate and iterate on predictive models for candidate generation and ranking (e.g., Click Through Rate and Conversion Rate prediction), including real-time data pipelines, feature engineering, model optimization and innovation.\r\nDesign and build supporting/debugging tools as needed.\r\nMinimum Qualifications\r\nBachelor's degree or higher in computer science or a related field.\r\n3+ years of experience with a solid foundation in data structure and algorithm design, and proficiency in one of the programming languages such as Python, Java, C++, R, etc.\r\nKnowledge of common machine/deep learning, causal inference, and operational optimization algorithms (classification, regression, clustering, mathematical programming, heuristic algorithms).\r\nExperience with at least one framework of TensorFlow, PyTorch, or MXNet and its training and deployment details, including mixed-precision training and distributed training.\r\nFamiliarity with big data frameworks; preference for those experienced with MR or Spark.\r\nPreferred Qualifications\r\nExperience in recommendation systems, online advertising, ranking, search, information retrieval, natural language processing, large-scale data mining, or related fields.\r\nPublications at KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS, or experience in data mining/machine learning competitions such as Kaggle or KDD Cup.\r\nCompensation\r\nThe base salary range for this position in San Jose is $150,000 – $316,800 annually. Compensation may vary outside of this range depending on qualifications, skills, and experience. Additional discretionary bonuses, incentives, and restricted stock units may also be provided.\r\nBenefits\r\nMedical, dental, and vision insurance immediately upon hire.\r\n401(k) savings plan with company match.\r\nPaid parental leave.\r\nShort-term and long-term disability coverage.\r\nLife insurance.\r\nWell-being benefits.\r\n10 paid holidays per year, 10 paid sick days per year, and 17 days of paid personal time (prorated on hire with increasing accruals by tenure).\r\nEEO Statement\r\nQualified 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.\r\nThe following duties are considered to have a direct, adverse, or negative relationship with the criminal history of applicants. The presence of a criminal record may result in a withdrawal of the conditional offer of employment:\r\nInteracting and occasionally having unsupervised contact with internal/external clients or colleagues.\r\nAppropriately handling and managing confidential information, including proprietary and trade-secret information and access to information technology systems.\r\nExercising sound judgment.\r\nJ-18808-Ljbffr","company":"Tik Tok","rawCompany":"tik tok","city":"San Jose","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-16T02:15:19.856Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer, Recommendation - E-Commerce","description":"Machine Learning Engineer, Recommendation - E-Commerce\r\nLocation: San Jose\r\nEmployment Type: Regular\r\nJob Code: A256265A\r\nResponsibilities\r\nResponsible for the build and design of optimization algorithm strategies for large-scale e-commerce recommendation algorithm pipeline.\r\nBuild long and short term user interest models, analyze and extract relevant information from large amounts of data and design algorithms to explore users' latent interests efficiently.\r\nDesign, develop, evaluate and iterate on predictive models for candidate generation and ranking (e.g., Click Through Rate and Conversion Rate prediction), including real-time data pipelines, feature engineering, model optimization and innovation.\r\nDesign and build supporting/debugging tools as needed.\r\nMinimum Qualifications\r\nBachelor's degree or higher in computer science or a related field.\r\n3+ years of experience with a solid foundation in data structure and algorithm design, and proficiency in one of the programming languages such as Python, Java, C++, R, etc.\r\nKnowledge of common machine/deep learning, causal inference, and operational optimization algorithms (classification, regression, clustering, mathematical programming, heuristic algorithms).\r\nExperience with at least one framework of TensorFlow, PyTorch, or MXNet and its training and deployment details, including mixed-precision training and distributed training.\r\nFamiliarity with big data frameworks; preference for those experienced with MR or Spark.\r\nPreferred Qualifications\r\nExperience in recommendation systems, online advertising, ranking, search, information retrieval, natural language processing, large-scale data mining, or related fields.\r\nPublications at KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS, or experience in data mining/machine learning competitions such as Kaggle or KDD Cup.\r\nCompensation\r\nThe base salary range for this position in San Jose is $150,000 – $316,800 annually. Compensation may vary outside of this range depending on qualifications, skills, and experience. Additional discretionary bonuses, incentives, and restricted stock units may also be provided.\r\nBenefits\r\nMedical, dental, and vision insurance immediately upon hire.\r\n401(k) savings plan with company match.\r\nPaid parental leave.\r\nShort-term and long-term disability coverage.\r\nLife insurance.\r\nWell-being benefits.\r\n10 paid holidays per year, 10 paid sick days per year, and 17 days of paid personal time (prorated on hire with increasing accruals by tenure).\r\nEEO Statement\r\nQualified 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.\r\nThe following duties are considered to have a direct, adverse, or negative relationship with the criminal history of applicants. The presence of a criminal record may result in a withdrawal of the conditional offer of employment:\r\nInteracting and occasionally having unsupervised contact with internal/external clients or colleagues.\r\nAppropriately handling and managing confidential information, including proprietary and trade-secret information and access to information technology systems.\r\nExercising sound judgment.\r\nJ-18808-Ljbffr","datePosted":"2026-07-16T02:15:19.856Z","dateModified":"2026-07-16T02:15:19.856Z","hiringOrganization":{"@type":"Organization","name":"Tik Tok","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Jose","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"c0eb4828814bde7fd39c5b4b"},"url":"https://jobsearcher.com/jobs/c0eb4828814bde7fd39c5b4b"}}