Senior Software Engineer, Machine Learning

Overview

Senior Software Engineer for the Machine Learning domain, working on ML infrastructure and modeling to improve ad performance and relevance.

What you'll do

• Build and manage the model lifecycle including feature engineering, training, versioning, deployment, online serving/evaluation, and prediction monitoring.
• Identify and generate reusable features for multiple use cases and models.
• Develop and evaluate algorithms using techniques including decision trees, logistic regression, neural networks, and Bayesian analysis to improve performance, quality, and accuracy.
• Perform production operations including systems debugging, performance measurement, and optimization on large production clusters.
• Collaborate with product managers, data scientists, and other engineers to deliver solutions.
• Continuously learn and adapt to emerging technologies and industry trends.

What you'll need

• Minimum 10 years of total experience.
• Bachelor’s, Master’s, or PhD in Computer Science, Statistics, or a related field.
• Applied machine learning experience on real use cases (bonus for ad tech-related use cases).
• Strong coding and software development experience using Spark, Python, and Java.
• Familiarity with real-time model evaluation under low latency constraints.
• Familiarity with distributed ML frameworks such as Spark-MLlib and TensorFlow.
• Ability to work with large-scale computing, data analysis systems, and modeling environments (e.g., Spark, Hive, Aerospike, ScyllaDB).

Details

• Hybrid work approach: generally work in the office Monday through Thursday; Fridays are generally flexible for remote work with exceptions.