Machine Learning Engineer II (Growth & ML)

Role Overview

The Machine Learning Engineer II will work alongside Senior and Staff engineers to build and maintain production ML pipelines, contribute to model development, and grow into a well-rounded ML engineer who bridges data science and software engineering.

What You Will Do

Build and maintain end-to-end ML pipelines for training, evaluation, and batch inference across use cases such as identity resolution, audience segmentation, and content affinity modeling.

Why It Might Be a Fit

The ideal candidate will have 2–4 years of industry experience in machine learning, data science, or ML engineering, strong Python proficiency, and hands-on experience with Spark/PySpark or equivalent large-scale data processing.

Requirements

• 2–4 years of industry experience in machine learning, data science, or ML engineering
• Strong Python proficiency
• Hands-on experience with Spark/PySpark or equivalent large-scale data processing
• Proficiency in SQL and familiarity with cloud data warehouses/lakehouses (Snowflake or Databricks)
• Experience with experiment-tracking tools (MLflow, Weights & Biases, or similar)
• Solid grasp of core ML concepts: classification, regression, ranking, embeddings, and model evaluation; plus strong CS fundamentals (data structures, algorithms, clean code)
• Bachelor’s degree in Computer Science, Statistics, Engineering, or a related quantitative field (or equivalent practical experience)

Benefits

• A Great Place to work
• Equal opportunity employer
• Fast track growth opportunities