Staff Machine Learning Engineer, ML Platform

What you'll do

• Lead and deliver complex ML infrastructure initiatives, including multi-region model serving, training pipelines, and CI and deployment tooling.
• Set the platform’s technical direction and production quality standards; lead incident response and improve reliability and cost efficiency.
• Coordinate with partner teams, review designs and code, mentor engineers and data scientists, and connect technical decisions to business outcomes.

What they ask for

• 8+ years building and operating distributed production systems, including deployment and operations, CI/CD, and infrastructure as code.
• Hands-on experience with production ML workloads, such as training pipelines, model serving, feature systems, or ML platform tooling.
• Technical leadership experience setting team direction, leading multi-quarter cross-team initiatives, and developing senior engineers.
• Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and cost.

Nice to have

• Experience with queueing and orchestration systems, ML platform tooling, or the listed stack: Python, Ruby on Rails, MongoDB, Redis, Kubernetes.
• Experience with SOX or HIPAA compliance, or customer engagement, personalization, or marketing technology.

Pay

$184,000 and $314,000/year USD (base salary); $204,000 and $348,000/year USD (On Target Earnings, including bonus or commission)

Tools

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

AI focus

Build and operate ML and AI-enhanced marketing solutions, including customer-specific model training pipelines and prediction-serving systems. Deep modeling experience is a plus, not a requirement.