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Own and grow Fireworks AIs AWS co-sell motion: source and manage ACE-registered opportunities, run joint account mapping and events, author AWS-focused GTM plays and reference architectures, manage Marketplace/CPPO metrics, and maintain executive AWS relationships to drive enterprise AI revenue.

The AI Native Account Executive will drive adoption of generative AI solutions, work with technical teams to guide onboarding, and identify opportunities for growth within client accounts.

The Senior GTM Recruiter will manage full-cycle recruiting for Go-To-Market functions, collaborating with leaders to build talent pipelines and optimize AI-driven recruitment strategies.

The Head of Marketing Operations oversees the marketing tech stack, data governance, budgeting, and program management to ensure efficient marketing operations and pipeline generation.

Lead GTM engineering: own Salesforce and GTM tech stack, design quoting/CPQ and lead-to-revenue systems, build production agentic AI workflows for sales, and grow a high-performing GTM engineering team focused on scalable automation and rep productivity.

Own creation and scaling of Fireworkssystems integrator (SI) channel: originate strategic Tier-1 SI agreements, recruit and develop partners, design certification and enablement (inference, fine-tuning, RLHF), operate partner technical desk, embed Fireworks into SI playbooks, and measure pipeline and practice maturity.

As an Applied Machine Learning Engineer, develop, deploy, and optimize machine learning models while collaborating with cross-functional teams to enhance customer solutions.

Drive new business by developing and executing account strategies to sell Fireworks AI to large enterprises. Own full sales cycle from prospecting to procurement, generate pipeline, leverage partners, forecast accurately, maintain customer satisfaction and travel for client meetings as needed.

The Revenue Accounting Lead manages revenue accounting processes, ensures compliance with ASC 606, collaborates with various teams, and drives automation and improvements in revenue workflows.

Conduct open-ended ML research and reproduce/extend state-of-the-art models while building scalable distributed training infrastructure. Implement and optimize training loops, data pipelines, and communication across GPU clusters, translating research into robust, efficient code and collaborating with research scientists.