Staff Machine Learning Engineer

What you'll do

• Own design, deployment, and ongoing health of machine learning systems driving revenue
• Ensure production ML models are reliable, monitored, and continuously improving
• Implement CI/CD pipelines to accelerate model deployment
• Ship high-impact ML systems tied to measurable business outcomes
• Optimize ML infrastructure for scalability and cost-efficiency
• Facilitate smooth cross-functional delivery between data science, engineering, and product teams

Requirements

• 6+ years of experience building and deploying ML models in production environments
• Ownership of full ML lifecycle from training through inference, monitoring, and iteration
• Strong proficiency in Python and SQL for model development, data manipulation, and pipeline work
• Experience with Spark for large-scale distributed data processing
• Hands-on experience with AWS (S3, EC2, Lambda, SageMaker) and cloud-native ML workflows
• Comfortable provisioning and managing cloud infrastructure programmatically
• Familiarity with MLOps stack including Databricks, Feature Stores, Kubernetes, Kubeflow, MLflow
• Experience building offline and online training and inference pipelines for real-time systems
• Strong understanding of CI/CD practices applied to ML including model versioning, automated testing, deployment pipelines, and rollback strategies
• Preferred: Ad tech or digital advertising experience with auction dynamics, bid optimization, CTR/viewability prediction, or audience targeting models
• Preferred: Experience with Go for performance-sensitive production services

Tech stack