Braze
Enterprise · Marketing automation
Currently tracking 16 active AI roles, up 102% versus the prior 4 weeks. Primary focus: Post-train · Engineering. Salary range $98k–$165k (avg $138k).
Enterprise · Marketing automation
| Title | Stage | AI score |
|---|---|---|
| Data Scientist, AI Deployment The Data Scientist, AI Deployment role at Braze focuses on designing and building end-to-end machine learning solutions for customer personalization. This involves managing the full ML pipeline from data transformation and model training to activation, with a strong emphasis on customer success and extending product capabilities. The role also involves shaping the AI product strategy and roadmap, particularly concerning reinforcement learning algorithms. | Post-trainAgent | 7 |
| Senior Forward Deployed Data Scientist, AI Deployment Senior Forward Deployed Data Scientist, AI Deployment role at Braze, focusing on customer-facing AI implementations. This role involves collaborating with customers and internal teams on ML model configuration, data pipelines, and improving architecture. It also includes working with the RL pipeline development team and contributing to product strategy. The goal is to ensure successful adoption and measurable outcomes for customers using Braze's AI capabilities. |
| ServePost-train |
| 7 |
| Forward Deployed Data Scientist, AI Deployment The Forward Deployed Data Scientist, AI Deployment role at Braze focuses on partnering with customers to implement and ensure success with BrazeAI. This involves defining use cases, integrating data, setting up pipelines, configuring ML models, and improving architecture. The role also involves refining reinforcement learning algorithms, contributing to product strategy through customer insights, and providing ongoing technical expertise for customer adoption and success. The position requires strong Python, ML libraries, SQL, and ML pipeline experience, along with engineering best practices. | AgentData | 7 |