Staff Applied Scientist

Braze•New York, NY

19h•$184,000 - $299,812•Hybrid

About The Position

Braze is seeking a Staff Machine Learning Engineer to join our Predictive and Generative AI (PGAI) team. The team's mission is to deliver a truly engaging and personalized customer experience through the creation of ML and AI enhanced marketing solutions. We own those solutions end to end, from the models and the flexible training pipelines that build them for each customer to the high-throughput APIs that serve predictions into our messaging systems. You will help set the scope of what is possible for customer engagement at scale, and from that space of possibilities you will lead solutions from prototype to product and build the ML platform that runs them. As the Staff Engineer on the team, you will: Identify and drive the transformative initiatives that change what the team can deliver, whether that's replatforming how we train and serve models, redefining how data science ships to production, or retiring a generation of infrastructure Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex initiatives yourself from design through production. Current examples include distributed model training and serving, model lifecycle management, and the pipelines that keep hundreds of customer-specific models healthy across regions Own the team's technical vision and quality bar. Set direction across the product portfolio and the ML platform, define best practices, and anticipate problems before they reach production Drive initiatives that span teams. Our solutions ship into messaging, analytics, and data platform surfaces, and you carry the technical relationships with those teams Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership

Requirements

8+ years building ML systems in production, with hands-on depth across data science, ML engineering, and ML operations. You have designed and trained models yourself, built the pipelines and services that run them, and operated them under production load
A technical leader who has owned direction for a team, led multi-quarter initiatives across team boundaries, and grown senior engineers, all while keeping a high personal output
Deep experience prototyping, refining, and deploying predictive models (supervised and unsupervised learning, neural networks, recommenders) with frameworks such as PyTorch and Tensorflow
Strong distributed systems fundamentals, designing for scale, reliability, and cost on the billions of daily data points our customers generate
An effective communicator, both verbal and written, whose designs and recommendations build consensus and drive forward decision making

Nice To Haves

Recommender systems, multi-armed bandits, or uplift modeling in production
ML platform tooling such as MLflow or another model registry, Ray, feature stores, or ML observability
Experience in our stack (Python, Ruby on Rails, MongoDB, Redis, Kubernetes)
Customer engagement, personalization, or marketing technology domain experience

Responsibilities

Identify and drive the transformative initiatives that change what the team can deliver, whether that's replatforming how we train and serve models, redefining how data science ships to production, or retiring a generation of infrastructure
Build and ship at high velocity. Staff at Braze is a hands-on delivery role; you carry the most complex initiatives yourself from design through production. Current examples include distributed model training and serving, model lifecycle management, and the pipelines that keep hundreds of customer-specific models healthy across regions
Own the team's technical vision and quality bar. Set direction across the product portfolio and the ML platform, define best practices, and anticipate problems before they reach production
Drive initiatives that span teams. Our solutions ship into messaging, analytics, and data platform surfaces, and you carry the technical relationships with those teams
Raise the team's engineering quality through design review, code review, and production readiness for ML systems, and mentor other senior engineers and data scientists
Connect technical decisions to customer and business outcomes, and represent the team's technical perspective to product and engineering leadership

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
A curated in-office employee experience, designed to foster community, team connections, and innovation
Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
Employee Resource Groups that provide supportive communities within Braze
Collaborative, transparent, and fun culture recognized as a Great Place to Work®