Braze
Staff Applied Scientist
$184K–$332K
Austin +1 · Staff · Full-time · Posted Sep 1, 2026
- Location
- Austin
New York City - Experience
- 8+ years building ML systems in production.
About the job
Leads the design, development, and production operation of machine-learning systems and platform capabilities for personalized customer engagement at scale.
What you'll do
- Lead complex ML initiatives from design through production, including model training, serving, and lifecycle pipelines.
- Set technical direction and quality standards for the team’s product portfolio and ML platform; improve engineering quality and mentor colleagues.
- Coordinate cross-team technical initiatives and connect engineering decisions to customer and business outcomes.
What they ask for
- 8+ years building production ML systems, with hands-on experience across data science, ML engineering, and ML operations.
- Experience prototyping, refining, and deploying predictive models using frameworks such as PyTorch and Tensorflow.
- Strong distributed systems fundamentals, including designing for scale, reliability, and cost.
- Technical leadership experience directing a team, leading cross-team multi-quarter initiatives, and developing senior engineers.
Nice to have
- Production experience with recommender systems, multi-armed bandits, or uplift modeling; or ML platform tools such as MLflow, Ray, feature stores, or ML observability.
- Experience with Python, Ruby on Rails, MongoDB, Redis, or Kubernetes; or customer engagement, personalization, or marketing technology.
Pay
USD 184,000–299,812/year base salary; USD 204,000–332,400/year On Target Earnings (OTE), including bonus or commission.
Tools
PyTorch, Tensorflow, MLflow, Ray, Python, Ruby on Rails, MongoDB, Redis
AI focus
Build and operate predictive and generative AI-enabled marketing solutions, including customer-specific models, training pipelines, and APIs that serve predictions for personalized customer engagement.
Model-written summary · the original posting is authoritative