About this role
The Predictive and Generative AI team at Braze builds machine learning and AI enhanced marketing solutions designed to deliver personalized customer experiences at global scale. Operating these solutions requires managing distributed training pipelines for individual customers alongside high-throughput APIs that serve predictions into multi-region messaging systems.
As a Staff Machine Learning Engineer, you will own the underlying platform by driving initiatives that make deploying, operating, and scaling machine learning fast, safe, and efficient. You will lead complex infrastructure projects from design to production, such as multi-region model serving fleets and customer-specific model pipelines, while also setting the technical vision and reliability standards for the team.
This role suits an experienced distributed systems engineer who enjoys hands-on delivery paired with technical leadership across teams. Someone who thrives in this position will combine a strong background in cloud infrastructure and Kubernetes with the ability to mentor senior engineers and connect technical decisions to broader business outcomes.
What you will do
- Identify and drive transformative initiatives that change how the team runs machine learning in production, including replatforming orchestration and overhauling deployment.
- Build and ship complex infrastructure projects from design through production as a hands-on delivery engineer.
- Own the platform's technical vision, set the production quality bar for model training and serving, and lead incident response for machine learning systems.
- Drive multi-quarter initiatives that span across team boundaries by coordinating shared infrastructure and deployment tooling with partner teams.
- Raise overall engineering quality through design reviews, code reviews, and production readiness checks while mentoring senior engineers and data scientists.
- Connect technical decisions to customer outcomes and represent the team's perspective to product and engineering leadership.
What you need
- Bring over eight years of experience building and operating distributed systems in production, with a strong focus on deployment and operations.
- Demonstrate hands-on experience with production machine learning workloads such as training pipelines, model serving, or feature systems.
- Act as a technical leader who has owned direction for a team and guided multi-quarter initiatives across organizational boundaries.
- Possess deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and cost management.
- Communicate effectively through verbal and written mediums to build consensus and drive decision-making.
Nice to have
- Queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
- ML platform tooling like MLflow, feature stores, or ML observability
- Experience in Python, Ruby on Rails, MongoDB, Redis, and Kubernetes
- Operating under compliance regimes such as SOX or HIPAA
- Customer engagement, personalization, or marketing technology domain experience
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 that include fertility benefits and equal paid parental leave
- Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
Skills and tech stack
Questions candidates ask
What is the pay range for this position?
For candidates based in the United States, the pay range is expected to be between $184,000 and $314,000 per year. The expected On Target Earnings range between $204,000 and $348,000 per year, including bonus or commission.
What kind of benefits are included?
The role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock units. Additional benefits include competitive compensation, retirement and employee stock purchase plans, flexible paid time off, and comprehensive medical, dental, vision, life, and disability coverage.
Where is the role located?
The position is based in New York City with a curated in-office employee experience designed to foster community, team connections, and innovation.