2 months ago
Base Salary
$184k - $300k/yr
Responsibilities
- Drive transformative initiatives involving ML training and serving, data-science production workflows, and infrastructure retirement.
- Design, build, deploy, and operate distributed model-training and model-serving systems, model lifecycle management, and pipelines for customer-specific models.
- Own the team’s technical vision, engineering quality bar, best practices, and production readiness for ML systems.
- Lead initiatives spanning messaging, analytics, and data platform teams and connect technical decisions to customer and business outcomes.
- Conduct design and code reviews, mentor senior engineers and data scientists, and represent the team’s technical perspective to leadership.
Requirements
- At least 8 years of hands-on experience building ML systems in production across data science, ML engineering, and ML operations.
- Experience designing and training predictive models, including supervised and unsupervised learning, neural networks, and recommenders, using frameworks such as PyTorch and TensorFlow.
- Strong distributed-systems fundamentals and experience designing for scale, reliability, and cost.
- Demonstrated technical leadership of team direction, multi-quarter cross-team initiatives, and senior engineer development while maintaining high personal output.
- Strong verbal and written communication skills that build consensus and support decision-making.
- Preferred experience with recommender systems, multi-armed bandits, uplift modeling, MLflow or other model registries, Ray, feature stores, ML observability, Python, Ruby on Rails, MongoDB, Redis, Kubernetes, or customer engagement and personalization technology.
Benefits
- Competitive compensation that may include equity, retirement and employee stock purchase plans, and flexible paid time off.
- Medical, dental, vision, life, disability, fertility, and equal paid parental leave benefits.
- Professional development through career pathing, learning platforms, and a yearly learning stipend.
- Hybrid ways of working with a curated in-office employee experience.
- Volunteer Week, donation matching, Employee Resource Groups, and a collaborative culture recognized as a Great Place to Work.
Tech Stack
Categories
About Braze
Braze builds a customer engagement platform used by marketing teams to orchestrate cross-channel messaging across mobile, email, web, and more. The company sells its software via SaaS subscriptions with analytics, segmentation, and journey orchestration. Founded in 2011 and headquartered in New York, Braze is a public company (NASDAQ: BRZE) with global offices.