Top AI & Machine Learning Jobs

Design and deploy reinforcement learning use cases and end-to-end ML pipelines, transforming customer data into production models. Provide technical guidance to customers, extend platform capabilities, partner with product on RL algorithms, and shape BrazeAI strategy and roadmap.

Lead AI Decisioning for Braze Japan, supporting sales as a technical SME and driving post-sale adoption. Deliver demos, discovery workshops, AI education, data integrations (Snowflake/Databricks/BigQuery), experimentation design, technical troubleshooting, and strategic business reviews to optimize AI-driven marketing outcomes.

Embed with non-revenue teams to discover high-leverage workflows, build and ship AI agents/automations on shared infrastructure, coach teams to self-sufficiency, productize durable solutions, and scale reproducible playbooks across the company.

Embed with functional teams to discover high-value workflows, build and ship AI agents and automations on shared infrastructure, coach teams to self-sufficiency, monitor adoption and quality, productize durable agents into the platform, and document reusable playbooks to scale transformation across the company.

As a Senior Lead AI Solutions Consultant, you'll drive revenue by promoting the BrazeAI portfolio, leading technical discussions, and conducting AI Academy workshops, while collaborating across teams to enhance Braze's offerings.

As a Senior Lead AI Solutions Consultant, you will drive revenue by promoting the Braze AI tools, collaborate with stakeholders, conduct AI Academy programs, and serve as a thought leader in AI technologies.

In this role, you will drive revenue by promoting Braze AI tools, perform proofs-of-concept, and lead educational programs while collaborating with various stakeholders.

As a Senior Lead AI Solutions Consultant, you will drive revenue through the adoption of BrazeAI tools, managing technical discussions, running proofs-of-concept, and educating clients on AI concepts.

The Data Scientist will design and build machine learning solutions, optimize for business value, and guide customer success through technical expertise and collaboration.

Design, implement, and scale production ML components and data pipelines using robust software engineering practices. Collaborate with customers and product teams to generalize use cases into platform features, deploy ML models to production, and maintain infrastructure (Kubernetes, Airflow, Terraform) and data services (BigQuery). Mentor teammates, write well-tested type-hinted code, and support successful customer implementations.