Machine Learning Engineer - Marketplace Growth (TikTok Global E-commerce Supply Chain Team)

$129,200 - $194,750/Yr

Tiktok - Seattle, WA

Full-time - Mid Level

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 part of the Global E-commerce Supply Chain Team, we are dedicated to enhancing clients' shopping experiences and reducing operational costs in the supply chain and logistics of TikTok E-commerce. We achieve this by developing end-to-end algorithm capabilities using machine learning, operations research, data mining, and causal inference methods. We are seeking a talented and motivated Machine Learning Engineer with expertise in marketplace growth to join our dynamic and fast-paced team. In this role, you will collaborate with cross-functional teams including data scientists, engineers, product managers, and business stakeholders to develop innovative solutions that unlock the value hidden within our data, leading to improved decision-making and operational efficiencies. You will utilize advanced machine learning techniques to analyze large-scale datasets, design and develop machine learning algorithms, and communicate findings effectively to both technical and non-technical stakeholders. This position offers an exciting opportunity to work at the intersection of technology and e-commerce, where you will be instrumental in driving growth and innovation within TikTok's global supply chain and logistics operations. You will be part of a team that values creativity, collaboration, and continuous learning, and you will have the chance to make a significant impact on the company's success.

Responsibilities

• Utilize advanced machine learning techniques to analyze large-scale datasets and identify meaningful patterns, correlations, and trends related to TikTok's global e-commerce supply chain and logistics operations.
• Design and develop machine learning algorithms for various tasks, including but not limited to customer segmentation, marketing, user characterization, and predictive modeling.
• Collaborate with data scientists, analysts, and subject matter experts 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 data mining 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

• Master's or advanced degree in Computer Science, Data Science, Statistics, or a related field.
• 3+ years experience as a Machine Learning Engineer, Data Scientist, and experience in Deep Learning is preferred.
• Work experience in user growth, marketing algorithms, recommendation algorithms, advertisement algorithms or related fields is preferred.
• Proficient in using SQL + Python and experience with data manipulation and analysis libraries, experience with TensorFlow or PyTorch is preferred.
• 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.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and convey technical concepts to non-technical stakeholders.
• Publications at KDD、NeurIPS、WWW、SIGIR、WSDM、CIKM、ICLR、ICML、IJCAI、AAAI and related conferences.

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 like Health Care, Limited Purpose and Dependent Care.
• 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.
• 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.
• Mental and emotional health benefits through our EAP and Lyra.
• 401K company match, gym and cellphone service reimbursements.