Staff Machine Learning Engineer, ML Platform

Braze is hiring a Staff Machine Learning Engineer to support its Predictive and Generative AI (PGAI) team. In this hybrid role based in Chicago, IL, you will own the machine learning platform beneath production systems, focused on deployment, operations, and scaling at global scale.

The work centers on production reliability and incident response for ML systems, alongside leading multi-quarter infrastructure initiatives that improve how ML is built, released, and monitored across teams.

What you’ll do

• Identify and drive transformative platform initiatives, including changes to how the team runs ML in production, such as replatforming queueing and orchestration, overhauling deployment and cloud identity, and retiring legacy infrastructure.
• Build and ship at high velocity in a hands-on capacity, carrying complex infrastructure initiatives from design through production.
• Set the platform’s technical vision and production quality bar, including guidance on how models are trained, deployed, served, and observed.
• Lead incident response for ML systems, and drive reliability and cost initiatives to keep the platform efficient at scale.
• Execute initiatives that span teams, maintaining technical relationships with partners supporting shared infrastructure, deployment tooling, and data systems.
• Improve engineering quality through design review, code review, and production readiness practices for ML systems.
• Mentor other senior engineers and data scientists, and translate technical decisions into customer and business outcomes while representing the team’s perspective to product and engineering leadership.

What you bring

• 8+ years building and operating distributed systems in production, with depth in deployment and operations.
• Hands-on experience with ML workloads in production.
• Technical leadership experience owning direction for a team and delivering multi-quarter initiatives across team boundaries while sustaining high personal output.
• Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and cost profiling for the systems you operate.
• Strong communication skills, both verbal and written, able to build consensus through designs and recommendations.

Bonus qualifications

• Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray.
• ML platform tooling such as MLflow (or another model registry), feature stores, or ML observability.
• Experience in Braze’s stack: Python, Ruby on Rails, MongoDB, Redis, Kubernetes.
• Operating under compliance regimes such as SOX or HIPAA.
• Customer engagement, personalization, or marketing technology domain experience.

Key technologies

• Celery, RabbitMQ, Kafka, Ray
• MLflow, Python, Ruby on Rails, MongoDB, Redis
• Kubernetes, SOX, HIPAA

Compensation and benefits

• Salary range: USD 184,000 - 314,000 per yearly (may include equity).
• Retirement and Employee Stock Purchase Plans.
• Flexible paid time off.
• Comprehensive benefit plans covering medical, dental, vision, life, and disability.
• Family services including fertility benefits and equal paid parental leave.
• Professional development with formal career pathing, learning platforms, and a yearly learning stipend.
• Curated in-office employee experience designed to foster community, team connections, and innovation.
• Volunteer Week and donation matching, plus Employee Resource Groups.
• Collaborative, transparent, and fun culture recognized as a Great Place to Work®.