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Top AI & Machine Learning Jobs in Austin, TX
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Build and productionize agentic workflows, RAG pipelines, AI services, backend systems, and ML pipelines for sales automation. Integrate Salesforce, quoting engines, data lakes, and internal platforms using scalable, event-driven architectures. Lead 0-to-1 development of tools for account research, lead prioritization, and quoting while ensuring reliability, observability, performance, and resilience across the GTM technology stack.
Top Skills:
Agentic AiAws LambdaAws SagemakerAws SqsGoJavaLlmsPythonRagSalesforce
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Leads Toast’s AI and analytics strategy for Enterprise Care. Owns the roadmap, evaluates and deploys AI-assisted support tools, develops operational intelligence products, and partners with Product, Engineering, and Data teams to move pilots into production. Establishes complexity and workload intelligence, assesses AI readiness, translates AI performance into measurable operational outcomes, and builds organizational AI literacy. The role requires extensive enterprise support or service-delivery leadership, hands-on production AI experience, operational data fluency, and the ability to drive trusted adoption among agents and executives.
Top Skills:
Analytics DashboardsGlanceLlmsMachine LearningSalesforceSalesforce Einstein
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Build and deploy statistical and machine learning models for the Toast platform. Collaborate with product, engineering, and business teams to identify opportunities, develop data-driven solutions, evaluate models, and communicate insights to stakeholders. Work in a fast-paced environment and contribute to production ML systems and experimentation.
Top Skills:
AirflowPythonPyTorchScikit-LearnSQLTensorFlow
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, demand forecasting, targeting, and personalization. Collaborate with engineers, product, and stakeholders to set architecture, metrics, and production best practices; mentor data scientists; lead experimentation and deploy/monitor models using cloud and MLOps tooling.
Top Skills:
AthenaAWSBedrockDistributed Data ProcessingDynamoDBGlueLlm Fine-TuningMlopsPythonPyTorchReal-Time InferenceRlhfSagemakerScikit-LearnSQLTensorFlow
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