Senior Machine Learning Engineer – Marketplace Growth

TikTok; Seattle (WA); On-site; USD 202,160 - 368,220; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid parental leave

Disability coverage

Life insurance

Job summary

TikTok is seeking a Senior Machine Learning Engineer to accelerate growth for merchants and creators in TikTok Shop. You will own end-to-end ML initiatives, build scalable data pipelines, and collaborate with data scientists, product managers, and business stakeholders to drive measurable growth.

You should bring deep knowledge of ML, feature engineering, and large-scale data processing with Hadoop/Spark, and communicate complex results to non-technical teams.

Qualifications

• Strong motivation to drive business growth through ML.
• Proficient in SQL and Python for data manipulation.
• Experience with Hadoop/Spark for large-scale data mining.
• Solid ML/DL knowledge including feature engineering and evaluation.
• Strong analytical and problem-solving skills on unstructured data.

Responsibilities

• Apply ML to analyze large datasets for merchant/creator growth.
• Collaborate with data scientists, PMs, and stakeholders to define objectives.
• Apply feature engineering to derive useful features and embeddings.
• Develop scalable data pipelines for ML tasks and ensure data quality.
• Evaluate ML approaches and recommend best solutions based on performance.
• Communicate findings to both technical and non-technical audiences.

Skills

SQL

Python

Big data processing

Machine learning concepts

Data analysis

Education

Master's degree in CS/Data Science/Statistics

Tools

Hadoop

Spark

Job description

TikTok is seeking a Senior Machine Learning Engineer to accelerate growth for merchants and creators in TikTok Shop. You will own end-to-end ML initiatives, build scalable data pipelines, and collaborate with data scientists, product managers, and business stakeholders to drive measurable growth.

You should bring deep knowledge of ML, feature engineering, and large-scale data processing with Hadoop/Spark, and communicate complex results to non-technical teams.