Staff Machine Learning Engineer, ML Platform

Braze is hiring a Staff Machine Learning Engineer for the Predictive and Generative AI (PGAI) team to own the ML platform underneath production ML and drive reliability at global scale.

Responsibilities

• Identify and lead major initiatives that change production ML operations, including replatforming queueing and orchestration, overhauling deployment and cloud identity, or retiring infrastructure components
• Ship high-impact infrastructure and ML platform changes at high velocity, with direct hands-on ownership of complex initiatives from design through production
• Own the platform technical vision and production quality bar, including direction for training, deployment, serving, and observability
• Lead incident response for ML systems and drive reliability and cost improvements to keep the platform efficient at scale
• Coordinate and deliver cross-team initiatives leveraging shared infrastructure, deployment tooling, and data systems owned with partner teams
• Improve engineering quality through design review, code review, and production readiness practices for ML systems
• Mentor 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

Requirements

• 8+ years building and operating distributed systems in production, with depth in deployment and operations
• Hands-on production experience with ML workloads
• Proven technical leadership: owned team direction, led multi-quarter initiatives across team boundaries, and grew 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 workloads
• Strong verbal and written communication skills, able to build consensus and drive forward decision-making
• Bonus: Experience with queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
• Bonus: Experience with ML platform tooling such as MLflow or other model registry tools, feature stores, or ML observability
• Bonus: Experience with Braze stack: Python, Ruby on Rails, MongoDB, Redis, Kubernetes
• Bonus: Experience operating under compliance regimes such as SOX or HIPAA
• Bonus: Experience in customer engagement, personalization, or marketing technology domains

Technology Focus

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

Location and Compensation

• Location: Chicago, IL (hybrid)
• Salary: USD 184,000 - 314,000 per year
• Minimum experience: 8 years

Benefits

• 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
• Curated in-office employee experience designed to foster community, team connections, and innovation
• Opportunities to give back, including annual Volunteer Week and donation matching
• Employee Resource Groups
• Collaborative, transparent, and fun culture recognized as a Great Place to Work®