Staff Applied Scientist
WHAT YOU'LL DO
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
WHO YOU ARE
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
Bonus:
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
For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $184,000 and $299,812/year with an expected On Target Earnings (OTE) between $204,000 and $332,400/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.