Top AI & Machine Learning Jobs

Design, build, and operate production AI automations and agentic workflows for Toast’s customer care systems. Integrate LLMs with Salesforce Service Cloud, Amazon Connect, and workflow platforms; develop autonomous actions with human oversight; test, monitor, and improve system reliability, accuracy, latency, and cost. Collaborate with software engineers, Salesforce developers, and care operations stakeholders to translate workflows into scalable intelligent solutions.

Build AI workflows, agents, and customer-facing web experiences that accelerate website production and improve conversion. The role involves optimizing Contentful-based processes, configuring chat, enrichment, voice AI, and personalization tools, running experiments, establishing AI guardrails, monitoring performance, and training marketing teams on reusable AI systems. Collaboration spans Web Platform, CRO, SEO, product marketing, legal, privacy, and brand teams.

Design, build, deploy, and maintain resilient, scalable backend services and platform components for Toast's Voice AI platform. Lead cross-cutting architecture and projects, integrate AI platforms (LLMs), implement observability and evaluation for AI systems, set engineering standards, and mentor engineers.

Build and maintain AI platform infrastructure, including LLM proxies, AI key management, observability pipelines, autonomous agents, MCP services, and an internal plugin marketplace. Develop reliable backend systems and developer tooling, collaborate across engineering and product teams, and promote agentic development practices. The role requires experience with scalable services, LLM-powered agents, distributed systems, cloud infrastructure, prompt engineering, and AI coding assistants.

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.

Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, forecasting, targeting, and personalization. Collaborate with engineers and product teams, set modeling and productionization standards, mentor data scientists, guide architecture and experimentation, and apply cloud and MLOps best practices to drive measurable product and business impact.

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.

Lead architecture and implementation of AI agents and infrastructure for the Team domain. Define scalable, secure designs, partner with engineering and product, write code and prototypes, resolve performance bottlenecks, establish agent/ spec-driven patterns, and mentor engineers to deliver mission-critical SaaS systems.