Staff Machine Learning Engineer, ML Platform

What you'll do

• Lead major infrastructure initiatives and deliver complex ML platform changes from design through production.
• Set technical direction and production quality standards; lead incident response and improve reliability and cost efficiency.
• Coordinate across partner teams, review designs and code, mentor senior engineers and data scientists, and connect technical choices to customer and business outcomes.

What they ask for

• 8+ years building and operating distributed production systems, including deployment and operations.
• Hands-on experience with production ML workloads, such as training pipelines, model serving, feature systems, or ML platform tooling.
• Technical leadership across team direction and multi-quarter initiatives, plus experience growing senior engineers while maintaining strong individual contribution.
• Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and cost.

Nice to have

• Queueing/orchestration systems, ML platform tooling, or experience with the listed stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes).
• Experience with compliance regimes such as SOX or HIPAA, or customer engagement, personalization, or marketing technology.

Pay

$184,000 and $314,000/year USD — base pay range; $204,000 and $348,000/year USD — expected On Target Earnings (OTE), including bonus or commission

Tools

Kubernetes, Celery, RabbitMQ, Kafka, Ray, MLflow, Python, Ruby on Rails

AI focus

Build and operate production ML systems for personalized customer experiences, including customer-specific model training pipelines and high-throughput prediction serving.