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Lead enterprise sales to frontier AI labs and Fortune 500s: build $20M+ pipelines, manage 20+ concurrent projects, navigate complex multi-stakeholder sales cycles, design tailored human-data solutions, execute pilots to scaled contracts, expand account wallet share, and create executive GTM narratives and thought leadership.

The role involves designing and maintaining reinforcement learning environments, developing containerized execution environments, managing integrations, and collaborating with data operations for AI training.

As an Applied Research Engineer, you'll develop frameworks for autonomous agents, design data programs, and collaborate with AI researchers to advance capabilities and publish results.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

Lead and grow a team of Technical Program Managers who run customer data projects end-to-end: staffing cadence, project setup, throughput and margin tracking, AR/billing hygiene, Airtable as system of record, onboarding TPMs, operational playbooks, and escalation for delivery risk. Serve as a player-coach partnering with Deployment Leads, FDE Manager, and GMs to ensure projects are staffed and delivered reliably.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Own end-to-end delivery of complex customer AI deployment programs: scope, technical design, staffing, execution, and unit economics. Coordinate TPMs, engineers, and cross-functional teams; manage margin, risk, timelines, and quality. Establish operating cadence, dashboards, and playbooks to scale deployments and serve as the customer's primary delivery contact.

Lead and grow a team of Forward Deployed Engineers (FDEs) to scope technical data programs, design pipelines and measurement, write instructions, and ensure data quality. Own hiring, onboarding, staffing, craft standards, tooling for reuse, and cross-functional alignment to keep FDEs focused on high-level technical work and career development.

Own day-to-day execution of customer data projects: set up projects, onboard and orchestrate data trainers via Pod Leads, run calibration and staged ramps, track fulfillment and project margin, operate billing/AR, keep Airtable current, coordinate FDEs/FDRs, identify and mitigate delivery risks, and ensure on-time, quality delivery.

Work post-sale with enterprise customers to implement and scale Labelbox data pipelines, advise on ML/LLM architecture and integrations (API, SSO, SaaS), manage onboarding and implementations, mentor users, drive product feedback and customer references, and partner with sales and product teams to realize ML goals.