Staff Machine Learning Engineer, ML Platform

Braze is looking for a Staff Machine Learning Engineer for its Predictive and Generative AI (PGAI) team. In this Staff role, you will own the machine learning platform beneath production systems, enabling fast, safe, efficient deployment, operations, and scaling at a global level. You will also drive production reliability and incident response for ML systems while leading complex infrastructure initiatives.

What you’ll do

• Identify and lead transformative production ML initiatives, including options such as replatforming queueing and orchestration, overhauling deployment and cloud identity, or retiring legacy infrastructure.
• Build and ship at high velocity with hands-on delivery, carrying complex infrastructure work personally from design through production.
• Own the platform technical vision and production quality bar by setting direction for how models are trained, deployed, served, and observed; lead incident response for ML systems; and drive reliability and cost efforts to keep the platform efficient at scale.
• Drive initiatives that span teams, partnering with groups that own shared infrastructure, deployment tooling, and data systems, and managing the technical relationships across those teams.
• Improve engineering quality through design review, code review, and production readiness for ML systems, while mentoring other senior engineers and data scientists.
• Translate technical decisions into customer and business outcomes, and represent the team’s technical 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 running ML workloads in production.
• Technical leadership that includes owning direction for a team, leading multi-quarter initiatives across team boundaries, and growing senior engineers while maintaining high personal output.
• Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of the systems you operate.
• Strong verbal and written communication skills that help designs and recommendations build consensus and move decisions forward.

Bonus (preferred)

• Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray.
• ML platform tooling such as MLflow or other model registry, feature stores, or ML observability tools.
• 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.

Technology areas

• 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 year.
• Competitive compensation that 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 supported by formal career pathing, learning platforms, and a yearly learning stipend.
• A curated in-office employee experience designed to foster community, team connections, and innovation.
• Volunteer opportunities including an annual company-wide Volunteer Week and donation matching.
• Employee Resource Groups that provide supportive communities within Braze.

Location: Chicago, IL (hybrid). Experience level: 8+ years.