2 months ago
Base Salary
$184k - $300k/yr
Responsibilities
- Lead transformative initiatives involving model training and serving, data science production workflows, and infrastructure modernization.
- Design, train, deploy, and operate distributed machine-learning models and services under production load.
- Build model lifecycle management and pipelines supporting hundreds of customer-specific models across regions.
- Own the technical vision, direction, best practices, and quality standards for the ML product portfolio and platform.
- Drive technical initiatives across messaging, analytics, and data platform teams.
- Improve engineering quality through design reviews, code reviews, production readiness, and mentoring.
- Connect technical decisions to customer and business outcomes and represent the team to product and engineering leadership.
Requirements
- 8+ years of experience building production ML systems with hands-on depth in 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.
- Technical leadership experience owning team direction, leading cross-team multi-quarter initiatives, and developing senior engineers.
- Strong verbal and written communication skills that support consensus-building and decision-making.
- Preferred experience with recommender systems, multi-armed bandits, uplift modeling, MLflow or another model registry, Ray, feature stores, ML observability, Python, Ruby on Rails, MongoDB, Redis, Kubernetes, and customer engagement or personalization technology.
Benefits
- Competitive compensation that may include equity, plus retirement and employee stock purchase plans.
- Flexible paid time off and comprehensive medical, dental, vision, life, and disability benefits.
- Fertility benefits and equal paid parental leave.
- Professional development through career pathing, learning platforms, and a yearly learning stipend.
- Hybrid ways of working and a curated in-office employee experience.
- Volunteer Week, donation matching, Employee Resource Groups, and a collaborative workplace culture.
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.