Top AI & Machine Learning Jobs

Lead Braze’s Applied AI Architects across GTM and corporate functions. Build and develop a senior technical team, manage the engagement portfolio, prioritize and measure AI initiatives, maintain hands-on involvement in agent design and delivery, and partner with product, technology, and executive leaders to scale successful solutions. Define the operating model and career framework for this emerging role category while driving measurable business outcomes such as sales ramp time, quota capacity, and competitive win rate.

Own the ML platform powering production training pipelines, model serving, deployment, orchestration, observability, and multi-region scaling. Drive major infrastructure initiatives, improve reliability and cost efficiency, lead incident response, collaborate across teams, and set the technical vision for ML operations. The role is hands-on, requiring production distributed-systems expertise, Kubernetes and cloud infrastructure knowledge, technical leadership, mentoring, and strong communication.

Own and evolve Braze’s ML platform for globally scaled training pipelines, model serving, deployment, orchestration, and observability. Lead complex infrastructure initiatives, improve reliability and cost efficiency, manage incident response, and establish production quality standards. Partner across teams, shape technical strategy, mentor senior engineers and data scientists, and connect platform decisions to customer and business outcomes.

Own and evolve Braze’s ML platform for production-scale training, deployment, serving, observability, reliability, and cost efficiency. Lead complex infrastructure initiatives, including multi-region model serving, customer-specific model pipelines, CI/CD tooling, orchestration, and cloud identity. Set technical direction, manage incidents, collaborate across teams, improve engineering quality, mentor senior engineers and data scientists, and connect platform decisions to business outcomes.

Own and evolve Braze’s ML platform for training, deploying, serving, and monitoring models at global scale. Lead complex infrastructure initiatives, multi-region model serving, CI/CD, orchestration, reliability, cost optimization, and incident response. Set technical direction, improve production quality, collaborate across teams, mentor senior engineers and data scientists, and connect platform decisions to business outcomes.

Lead the technical vision and delivery of production machine learning systems, including distributed training, model serving, lifecycle management, and customer-specific model pipelines. Drive cross-team initiatives, establish engineering best practices, improve ML platform reliability and scalability, mentor senior engineers and data scientists, and connect technical decisions to customer and business outcomes.

Lead end-to-end machine learning initiatives for Braze’s Predictive and Generative AI team. Design, train, deploy, and operate predictive models, distributed training and serving systems, customer-specific model pipelines, and high-throughput prediction APIs. Set technical direction and quality standards, drive cross-team initiatives, mentor engineers and data scientists, and connect ML platform decisions to customer and business outcomes.

Lead the technical vision and delivery of production machine learning systems, including distributed model training, serving, lifecycle management, and customer-specific model pipelines. Drive cross-team initiatives, establish engineering standards, review designs and code, mentor senior engineers and data scientists, and connect technical decisions to customer and business outcomes. Build scalable, reliable ML platforms and high-throughput prediction services supporting personalized customer engagement.

Leads end-to-end development of production machine learning systems, including model training, serving, lifecycle management, and high-throughput APIs. Drives technical vision, distributed ML platform initiatives, cross-team programs, engineering quality, and mentorship. Designs predictive and generative AI solutions at scale, ensuring reliability, cost efficiency, and alignment with customer and business outcomes.

Lead design and delivery of enterprise integrations, automation, and AI-enabled workflows across SaaS platforms. Architect scalable APIs, conversational IT/self-service experiences, and agentic LLM workflows while partnering with Security, Infrastructure, and Product to ensure governance, reliability, and operational excellence.