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As an Applied AI Inference Engineer, you will architect, build, and deploy AI applications, collaborating with customers throughout the development and deployment process, and enhancing ML projects.

Build in-house tools for post-training models, focusing on improving model efficiency using various ML techniques across the system stack.

The Program Manager will operationalize marketing campaigns, ensure flawless execution, improve documentation, and manage cross-functional alignment. Responsibilities include running marketing operations, QA for campaigns, reporting, and enhancing workflows for scalability.

As a Senior Software Engineer, you will manage Baseten's billing and revenue infrastructure, ensuring reliability and collaboration with finance and sales teams while evolving the billing platform.

Own and scale Baseten's paid acquisition engine: build funnel analytics and dashboards, design experiments across channels and creatives, scale high-performing campaigns to grow qualified pipeline while reducing CAC.

The Integrated Marketing Manager will lead multi-channel campaign strategies, project management, performance measurement, and collaborate across teams to enhance engagement and drive sales pipeline.

Partner with Sales and customers to run technical discovery, lead demos and scoping, design repeatable ML inference deployments across modalities, benchmark inference performance, and drive POC execution and stakeholder alignment.

Own and operate Baseten's internal AI stack, build and deploy custom AI agents and LLM-powered tools, evaluate third-party AI developer tools, instrument usage and measure impact on engineering productivity, and support engineering teams in adopting AI workflows.

The Sales Manager will lead a team of Account Executives, drive revenue growth, define go-to-market strategies, and collaborate cross-functionally to align products with customer needs.

Lead end-to-end development of new platform products: design developer-friendly APIs and abstractions, build and operate reliable backend services (auth, rate limiting, quotas, metering) with SLOs, improve performance and reliability, and mentor teammates while collaborating cross-functionally on ML infrastructure initiatives.