Tiktok - Seattle, WA

posted 27 days ago

Full-time - Senior
Seattle, WA
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. As a Senior Machine Learning Engineer in the E-commerce Merchant and Creator Growth team, you will play a pivotal role in expanding the number of merchants and creators on TikTok Shop. This involves developing end-to-end algorithmic capabilities utilizing machine learning, data mining, and causal inference methodologies. You will collaborate with cross-functional teams, including data scientists, product managers, and business stakeholders, to create innovative solutions that drive growth within the TikTok Shop ecosystem. In this dynamic and fast-paced environment, you will utilize advanced machine learning techniques to analyze large-scale datasets, identifying meaningful correlations and causal relationships that impact merchant and creator growth. Your responsibilities will include defining data mining objectives, applying feature engineering techniques, and developing scalable data pipelines to ensure data quality and availability. You will also evaluate and benchmark various machine learning approaches, staying updated with the latest advancements in the field to enhance the team's capabilities. Effective communication is key in this role, as you will need to convey findings and technical concepts to both technical and non-technical stakeholders, fostering a collaborative and data-driven decision-making culture. Your contributions will not only drive business growth but also support TikTok's mission of inspiring creativity and bringing joy to users around the globe.

Responsibilities

  • Utilize advanced machine learning techniques to analyze large-scale datasets and identify meaningful correlations and causal relations related to merchant and creator growth in TikTok Shop.
  • Collaborate with business stakeholders, product managers, and data scientists to define data mining objectives and develop strategies to address complex business problems and opportunities.
  • Apply feature engineering techniques to derive relevant features and embeddings from raw data and improve the performance of machine learning models.
  • Develop scalable and efficient data pipelines to preprocess and transform data for machine learning tasks, ensuring data quality, consistency, and availability.
  • Evaluate and benchmark different machine learning approaches, algorithms, and tools, and recommend the most appropriate solutions based on performance, scalability, and interpretability.
  • Stay updated with the latest advancements in data mining, machine learning, and related fields, and apply this knowledge to enhance the team's capabilities and identify new opportunities.
  • Communicate findings, insights, and technical concepts effectively to both technical and non-technical stakeholders, fostering a collaborative and data-driven decision-making culture.

Requirements

  • Highly self-motivated to drive business growth and foster technical advancement.
  • Proficient in using SQL and Python with experience in data manipulation.
  • Experience with big data processing frameworks (e.g., Hadoop, Spark) and distributed computing for efficient data mining on large-scale datasets.
  • Solid understanding of machine/deep learning concepts and techniques, including feature engineering, model evaluation, and optimization.
  • Strong analytical and problem-solving skills, with a demonstrated ability to handle and derive insights from complex and unstructured datasets.

Nice-to-haves

  • Master's or advanced degree in Computer Science, Data Science, Statistics, or a related field.
  • 5+ years experience as a Machine Learning Engineer or Data Scientist, with experience in causal machine learning preferred.
  • Work experience in user growth, marketing algorithms, recommendation algorithms, advertisement algorithms, or related fields preferred.
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and convey technical concepts to non-technical stakeholders.

Benefits

  • 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents, and a Health Savings Account (HSA) with a company match.
  • Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans.
  • Flexible Spending Account (FSA) options for Health Care, Limited Purpose, and Dependent Care.
  • 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) and 10 paid sick days per year.
  • 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.
  • Mental and emotional health benefits through EAP and Lyra.
  • 401K company match, gym and cellphone service reimbursements.
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